Abstract: Robotic palletizing requires the rapid generation of optimal packing plans and the corresponding robot programs within the tight time constraints imposed by mass customization and factory intralogistics. In this context, while the bin packing problem has been extensively studied in the literature, practical engineering tools that support flexible batch palletizing, from optimal packing definition to validated robot execution, remain limited. In this regard, the present paper proposes an integrated simulation framework that guides engineers in defining an optimal robotic palletizing process through a structured sequence of steps. Starting from the 3D model of an existing palletizing station and its input product mix, the framework, implemented as a set of interconnected Python modules within the RoboDK simulation platform, supports automated generation and assessment of actionable packing layouts, simulation-based verification of the robotic process, and generation of executable robot code that can be automatically transferred to the robotic palletizing cell within a Digital Twin oriented approach. An efficient heuristic method is introduced to solve 3D packing instances for box-type items on standard Europallets. The problem is initially formulated as a sequence of 2D packing problems solved through a Guillotine plus Best Fit strategy, iterating across layers to maximize pallet filling while improving load balancing. The framework is validated across multiple scenarios on an industrially representative case study involving a KUKA palletizing robot, a conveyor feeding system, and two auxiliary buffer pallets. Finally, an instruction streaming module enabling online execution of the validated code on the KUKA controller is presented. Overall, the results confirm the effectiveness of the proposed framework in accelerating process planning, virtual validation and programming activities while maintaining packing quality in realistic industrial scenarios.

Keywords: Bin packing | Engineering method | Instruction streaming | RoboDK | Robot simulation framework | Robotic palletizing

Abstract: Collaborative robotics is increasingly considered in manufacturing to improve efficiency while reducing operators physical and cognitive workloads. However, the lack of comprehensive methodologies has limited the consistent implementation of human–robot collaborative workstations across industries. Existing approaches are often fragmented, require robotics expertise, and pose challenges for non-experts, leading to suboptimal station designs and inefficient task allocation. This study presents a structured design framework to transition traditional assembly processes into collaborative ones. The framework provides a practical, scalable solution for optimizing collaborative workstations, balancing performance, ergonomics, and industrial applicability. It starts from the analysis of the assembly tasks, followed by classification and allocation between human operators and robots, and concludes with virtual prototyping and performance optimization through simulation using a commercial tool. The adopted methodology integrates task analysis, ergonomic assessment, and workspace design to ensure accessible and efficient implementation. Validated through two industrial case studies involving a gear pump and a worm gearbox, the approach demonstrated significant reductions in cycle time and notable improvements in the ergonomic working conditions.

Keywords: Collaborative assembly | Collaborative robotics | Human–robot simulation | Integrated design framework | Task allocation | Virtual prototyping

Abstract: Industry X.0 robotic manufacturing demands higher accuracy and flexibility, enabling continuously adaptive processes designed and optimized through simulations and Digital Twins. To achieve this level of flexibility and productivity in high value-added processes, where limited robot position accuracy becomes a critical constraint, advanced engineering methods and digital tools are required. These solutions must predictively compensate for inevitable robot positional accuracy errors, eliminating the need for manual pose refinement and enabling the generation of “first-time-right” robot code. This work aims to address these challenges by introducing an engineering tool capable of predictively correcting robot positioning inaccuracies across the workspace, enabling accurate point-to-point motion generation. It is intended for tasks with limited process interaction forces, where positioning errors are dominated by geometric, compliance, and joint-related effects. The tool leverages a multi-parameter Machine Learning (ML) error predictor trained on a reduced experimental dataset, minimizing data acquisition time and production downtime. Realized as a Python-based framework, it can be seamlessly integrated into commercial offline programming environments to automatically generate validated robot programs. The paper details the framework structure, focusing on the definition of the ML-based position error predictor, and its implementation on a robotic cell equipped with a high-payload KUKA robot and a FARO laser tracker. A preliminary experimental analysis identified payload, approach direction, and point location as the key operational parameters, accessible at the code level, that influence positioning accuracy. These insights guided feature selection and the design of reduced training datasets. In particular, a uniform spatial grid of only 64 points, corresponding to about one hour of measurement time, was sufficient to achieve near-optimal model accuracy. Several ML algorithms were compared, with the Tabular Prior-data Fitted Network achieving superior generalization on small datasets. Experimental validation on the KUKA robot showed up to a 98.4 % reduction in positioning error and consistent performance across all tested points, confirming the tool robustness and suitability for deployment across different industrial environments. All datasets, source code, and implementation scripts are openly released to enable reproducibility and facilitate industrial deployment.

Keywords: Engineering tool | Industrial robot | Machine learning | Offline compensation | Position accuracy | Robot simulation

Abstract: The design and management of Industry X.0 manufacturing systems is based on several simulation tools and digital models, used to predict and optimize the final performance. The lack of a seamless interoperability between such tools requires the development of a Digital Thread, a communication framework able to connect and synchronize digital models with the physical assets throughout their lifecycles. This study presents a novel Digital Thread based framework for the simulation and Virtual Commissioning of robotic systems, built on a Docker infrastructure integrated with Hadoop 3.2.0. It leverages AutomationML (AML) as a data exchange standard and the Robot Operating System (ROS) for distributed robotic control. The proposed architecture supports offline programming and facilitates the deployment of custom, multi-brand robotic systems, while enabling seamless integration of AML-based Digital Twins. The proposed methodology is validated on a large scale robotic manufacturing cell for aircraft fuselage assembly, demonstrating its capability in terms of performance validation, operational coordination, and optimization of production sequences.

Keywords: AutomationML | Engineering Methods | ROS | Simulation Framework | Virtual Prototyping

Abstract: Purpose – This paper aims to present a novel method and tool for evaluating the motion resolution of industrial robots, defined as the minimum effective motion increment, to enable behavior-informed design and optimization of high-precision industrial robotic systems. Design/methodology/approach – A high-precision laser interferometer is used to measure the joint motion resolution of a KUKA KR210 R2700 Prime robot, following an improved test procedure derived from the ISO 230 standard and an objective error-based identification method. The resulting joint maps are then used to build a prediction tool, implemented in Python and integrated with RoboDK to propagate joint-level resolution to pose- and direction-dependent end-effector Cartesian resolution estimates across the robot workspace. Findings – Results show that ISO 230 tests can mask intrinsic joint resolution in the micro-step range due to backlash-driven response flattening. The proposed test procedure highlights marked joint-dependent performance, with the first three joints generally exhibiting finer micro-step resolution and more stable step responses than the wrist joints. The Cartesian predictor reproduces measured micro-displacement trends with uncertainty envelopes. Originality/value – The paper provides an objective and repeatable approach that decouples intrinsic resolution from backlash, and introduces an efficient prediction tool for Cartesian resolution estimation, supporting improved system design as well as robot motion planning and compensation for precision manufacturing tasks.

Keywords: Backlash | Industrial robots | Laser interferometer | Least increment step | Motion resolution | Prediction tool

Abstract: This paper addresses the crucial aspect of position error modeling and compensation in industrial servomechanisms with the aim to achieve accurate control and high-performance operation in industrial robots and automated production systems. The inherent complexity and nonlinear behavior of these modules, usually consisting of a servomotor and a speed reducer, often challenge traditional analytical modeling approaches. In response, the study extensively explores the design and implementation of Machine Learning (ML) algorithms to obtain a comprehensive model of the Transmission Error (TE) in rotating vector reducers, which is a main source of robot motion accuracy errors. The ML models are trained with experimental data obtained from a special purpose test rig, where the reducer is tested under different combinations of input speed, applied load and oil temperature. In the second part of the work, the resulting predictive model, tailored to capture the intricate dynamics of the analyzed reducer, is imported into a programmable logic controller to enable online compensation strategies during the execution of custom motion profiles. Experimental tests are conducted using two distinct motion profiles: one generated with a cycloidal law, typical of industrial machinery, and the other extrapolated from the joints of an industrial robot during a pick-and-place task. The results demonstrate the effectiveness of the proposed approach, enabling accurate prediction and substantial reductions (over 90%) in the overall reducer TE through the implemented predictive model.

Keywords: Compensation approach | Machine learning | Predictive modeling | Servomechanism | Test rig | Transmission error

Abstract: Traditional industrial robots offer significant operational flexibility and adapt well to reconfigurable production systems, although they face limitations in applications demanding high motion performance and spatial positional accuracy. While novel manufacturing solutions supporting small batch productions of custom products are widely researched, they are not yet fully available at industrial level. With the aim to advance in this domain, the present work, conducted in the context of the EU project OPeraTIC, reports the development of a novel manipulator for advanced three-dimensional laser surface treatment of large industrial components. The proposed robotic platform presents a decoupled kinematic architecture, with direct drive actuation in all axes. Its open control ensures adaptability to diverse manufacturing scenarios, making it a versatile tool for modern production lines. Starting from the description of its embodiment design and mechanical layout, the paper delves into robot virtual prototyping focusing on kinematic and dynamics aspects. In particular, a detailed behavioral model covering direct and inverse kinematic calculations, also allowing the precise evaluation of all actuation forces/torques, has been developed using analytical approaches. The model is validated with a commercial solver imposing different spatial motions.

Keywords: dynamics | kinematics | multibody model | robotic design | simulation | virtual prototyping

Abstract: To ensure the geometric accuracy of wire arc additive manufacturing (WAAM) components, it is essential to analyze how process parameters influence the weld bead dimensions and shape. This paper presents a formal and repeatable procedure to entirely characterize the geometry of beads by enhanced full-coverage optical scanning with focus on multi-layered thin-walled closed specimens realized by the cold metal transfer (CMT) welding process. A series of circular specimens have been manufactured according to a DOE plan of process parameters, scanned with a GOM fringe projection 3D optical scanner, geometrically processed in the Rhinoceros 3D CAD environment, and analyzed by statistical indices according to the ANOVA approach. Average dimensions, lateral surface waviness, interaction between successive layers, and the torch switch-on/off zone of closed layer paths have been assessed. Numerical correlations between bead sizes and deposition parameters have been established. The obtained results also reveal shape and dimensional variability, highlighting the challenges in controlling geometry accuracy.

Keywords: 3D optical scanning | Bead geometry analysis | Cold metal transfer | Design methods | Geometry processing algorithm | Wire arc additive manufacturing

Abstract: Maintenance operators usually face complex challenges due to the complexity of modern sophisticated machinery and systems. Only highly experienced operators may have sufficient skills to perform recovery procedures properly and quickly; frequently, not expert operators need for assistance from the manufacturer’s after-sales. Therefore, very long recovery times, high maintenance costs, and temporary drop in production take place. In this context, augmented reality (AR) can offer valid support to non-expert operators involved in maintenance activities. In this work, a framework based on user experience (UX) design approach was developed for designing highly usable AR applications to guide operators in performing maintenance procedures safely and efficiently. The proposed framework has been applied to the H2020 European project titled “XMANAI – Explainable Manufacturing Artificial Intelligence”.

Keywords: augmented reality | Industry 5.0 | Operator 4.0 | transdisciplinary engineering | user experience design

Abstract: The fourth industrial revolution (I4.0) is driving the development of automated and intelligent manufacturing systems, but managing these systems poses challenges, especially for maintenance and process control. The emerging Industry 5.0 (I5.0) concept advocates for a human-centered approach, integrating human skills with advanced technologies to address such challenges. This study introduces a novel holistic evaluation of ergonomics, moving beyond traditional physical assessments to include cognitive ergonomics, thus providing a more comprehensive analysis of operator interactions with industrial systems. The proposed approach leverages Virtual Reality (VR) simulations combined with wearable devices to collect data on users’ movements and physiological parameters. This enables simultaneous evaluation of physical workload and cognitive demands, fostering early identification of ergonomic issues in the design process. Unlike traditional methods, our framework emphasizes a deeper integration of devices for enhanced data analysis, ensuring that both physical and cognitive factors are addressed. As a case study, the redesign of an automated packaging machine was undertaken. Results demonstrated significant ergonomic improvements, reducing the EAWS (European Assessment Work-Sheet) score (from 30% to 50% approx.) and incorporating cognitive ergonomics into the evaluation.

Keywords: digital simulation | ergonomics and human factors | Human-centered design | industry 5.0 | virtual maintenance | virtual reality

Abstract: Purpose – In Wire Arc Additive Manufacturing, the size and shape of the deposited material are affected by heat input, material deposition rate, orientation with respect to gravity, substrate conformation and the sequence of beads. The paper aims to investigate the geometric behavior of adjacent overlapping beads and proposes a model to predict the shape assumed in case of multiple beads deposition according to the succession of accumulation. Design/methodology/approach – Geometric curves such as parabolas, circular arcs, cosines and ellipses have been proposed in the literature to represent the resulting cross-section bead profiles, even though multiple beads deposition scenarios have been scarcely explored and, in most cases, restricted to simplified situations, such as planar substrates. Therefore, a generic geometric model for the bead profile based on a closed curve composed of two Hermite spans is proposed. Findings – The algorithm reliability was tested on circular specimens realized with a Fronius TPS 320i welding generator and on a set of documented cases from the literature. The results demonstrate that the Hermite curve-based model and the proposed algorithm can accurately reproduce various bead profiles in multi-bead and multi-layer deposition sequences. Originality/value – Thanks to the positioning of its control points, the Hermite curve exhibits the necessary variability in bead height, width, shape and contact angles with the substrate, offering greater flexibility in geometric approximation compared to existing models.

Keywords: Bead geometric modeling | Multi-bead deposition | Multi-layer deposition | Weld deposition | Wire arc additive manufacturing

Abstract: Industrial Robots (IRs) are typically employed as flexible machines to perform many types of repetitive and intensive tasks within fenced safe areas, ensuring high productivity and cost efficiency. However, their rigid programming approaches often pose challenges during cell commissioning and reset, hindering the implementation of self-reconfigurable systems. In addition, several production lines still need the presence of skilled operators to conduct assisted assembly operations and inspections. This motivates the growing interest in the development of innovative solutions for supporting safe and efficient human–robot collaborative applications. The manual guidance of the IR end-effector is a representative functionality of such collaboration, as it simplifies heavy-part manipulation and allows intuitive robot teaching and programming. The present study reports a sensor-based approach for enabling manual guidance operations with high-payload IRs and discusses its practical implementation on a production cell with an extended workspace. The setup features a KUKA robot mounted on a custom linear track actuated via Beckhoff technology to enable flexible assembly and machining operations. The developed logic and its software configuration, split into multiple control units to allow the manual guiding of both the 6-axis IR and the linear track unit, are described in detail. Finally, an experimental demonstration involving two users with different levels of expertise was conducted to evaluate the approach during target teaching on a physical cell. The results showed that the proposed manual guidance method significantly reduced task completion time by more than 55% compared with the conventional teach pendant, demonstrating the effectiveness and practical advantages of the developed framework.

Keywords: collaborative manufacturing | human–robot interaction | industrial robot | linear track | manual guiding

Abstract: The design of delta robots poses significant challenges as their mechanical behavior depends on a high number of dimensional parameters and dynamic factors. This is further compounded by the presence of demanding performance requirements, particularly in terms of position accuracy during high-dynamics motion tasks. By leveraging theoretical models, dynamic optimization techniques and advanced simulations, the present paper aims to streamline the design process, providing a structured engineering method and tool to address the dimensional synthesis of delta robots, encompassing kinematics, dynamics, link flexibility, and ball joint clearance. The systematic design process incorporates user requirements, including bounding box specifications, cycles per minute for pick-and-place operations, end-effector accuracy tolerance, maximum static payload, and cost minimization. The methodology involves an initial dynamic optimization phase employing a genetic algorithm to derive optimal dimensional parameters. Analytical models implemented in Matlab expedite the iterative optimization process. Then, the optimized design is virtually prototyped in RecurDyn flexible multibody simulation tool for validation by including the link flexibility and the effect of ball joint clearances. The iterative approach ensures that the final design aligns with user expectations. Additionally, the paper addresses motor selection based on torque requirements and proposes an approach for evaluating the robot performance in terms of maximum end-effector acceleration and payload. Finally, the efficacy of the tool is evaluated through a case study focused on designing a manipulator as an integral part of a collaborative research project with an industrial partner.

Keywords: Delta robot | Design tool | Industrial robotics | Multibody simulation | Optimization

Abstract: Industrial Robots (IR) are currently employed in several production areas as they enable flexible automation and high productivity on a wide range of operations. The IR low positioning performance, however, has limited their use in high precision applications, namely where positioning errors assume importance for the process and directly affect the quality of the final products. Common approaches to increase the IR accuracy rely on empirical relations which are valid for a single IR model. Also, existing works show no uniformity regarding the experimental procedures followed during the IR performance assessment and identification phases. With the aim to overcome these restrictions and further extend the IR usability, this paper presents a general method for the evaluation of IR pose and path accuracy, primarily focusing on instrumentation and testing procedures. After a detailed description of the experimental campaign carried out on a KUKA KR210 R2700 Prime robot under different operating conditions (speed, payload and temperature state), a novel online compensation approach is presented and validated. The position corrections are processed with an industrial PC by means of a purposely developed application which receives as input the position feedback from a laser tracker. Experiments conducted on straight paths confirmed the validity of the proposed approach, which allows remarkable reductions (in the order of 90%) of the orthogonal deviations and in-line errors during the robot movements.

Keywords: Error compensation | Experimental approaches | Industrial robots | Laser tracker | Path accuracy | Pose accuracy

Abstract: Wire Arc Additive Manufacturing is based on a welding torch usually attached to a robotic arm with multiple degrees of freedom. Robot-based additive manufacturing allows non-planar and non-uniform thickness layers to be deposited where the slices have non-constant thickness. Thus, in addition to the motion settings, fine regulations of the welding parameters become necessary to obtain variable bead heights in the same slice. This paper aims to evaluate the user-accessible welding parameters’ influence on the deposited material’s dimensions during continuous Cold Metal Transfer (CMT) and its variant named CMT Cycle Step. In particular, the height and width of beads are investigated by varying the travel speed and the wire-feed rate (continuous CMT), as well as the size of the droplets by varying the number of CMT cycles and the wire-feed rate (CMT Cycle Step). In particular, the characterization of the material deposited during the CMT Cycle Step is not deeply studied in the literature. The experimental specimens are measured and the obtained values are numerically processed to yield empirical formulas that link the dimensions of the deposited material with the selected process parameters. The results show that CMT Cycle Step is more stable than continuous CMT, which confirms its higher suitability for accurate manufacturing.

Keywords: Bead Modeling | Cold Metal Transfer | Experimental characterization | Wire and Arc Additive Manufacturing

Abstract: The study of an automated system for intralogistics requires an important use of time and resources, starting from the input data analysis up to the definition of the technical solution. While many commercial tools are available for testing and optimizing the plant performance during the advanced design stages, little work has been done concerning the workflow to be followed at the pre-sales design phase. In this context, the present paper focuses on the definition of the best practices for the correct preliminary definition of a robotic cell for palletization. To simplify and speed up the pre-sales feasibility study and estimate the performance of the proposed robotic system, an engineering approach based on a simplified theoretical model is reported and integrated within a dynamic calculation table. As the main output, the proposed tool calculates the robot saturation which is a key index for the plant preliminary definition.

Keywords: Design Tool | Industry 4.0 | Palletizing Robotic System | Performance Definition | Pre-Sales Design

Abstract: Planar slicing algorithms with constant layer thickness are widely implemented for geometry processing in Additive Manufacturing (AM). Since the build direction is fixed, a staircase effect is produced, decreasing the final surface finish. Also, support structures are required for overhanging portions. To overcome such limits, AM is combined with manipulators and working tables with multiple degrees of freedom. This is called Robot-Based Additive Manufacturing (RBAM) and it aims to increase the manufacturing flexibility of traditional printers, enabling the deposition of material in multiple directions. In particular, the deposition direction is changed at each layer requiring non-uniform thickness slicing. The total number of layers, as well as the volume of the support structures and the manufacturing time are reduced, while the surface finish and mechanical performance of the final product are increased. This paper presents an algorithm for non-uniform planar slicing developed in Rhinoceros and Grasshopper. It processes the input geometry and uses parameters to capture manufacturing limits. It mostly targets curved geometries to remove the need for support structures, also increasing the part quality.

Keywords: Multiaxial Deposition | Non-Uniform Slicing | Robot-based Additive Manufacturing

Abstract: Robotic cells are complex mechatronic systems whose final performance is determined by the interaction of the control logics with the mechanical behavior of the process. In this context it is fundamental to develop engineering methods and tools for the virtual prototyping of the cells that emulate both contributions. With such mechatronic digital models, it would be possible to replicate the real behavior of the systems and to optimize the cell productivity, up to building complete digital twins. This paper proposes an engineering method to develop realistic Virtual Prototypes of robotic cells including their geometry, operating logic, performance, and physical behavior. A case study on a robotic cell composed of two anthropomorphic robots for the flexible process of automatic assembly of industrial parts is presented to demonstrate the approach.

Keywords: Digital twin | Physics-based simulation | Robotic assembly | Virtual prototyping

Abstract: Robot-based additive manufacturing (RBAM) is an additive manufacturing (AM) technology powered by robotic manipulators. The material is deposited from a nozzle onto an initial surface, adding successive layers on top of each other and pouring it along multiple directions (multiaxial deposition) thanks to the dexterity of robots, often of the anthropomorphic type. Furthermore, it is possible to manufacture layers of non-uniform thickness, thus obtaining non-parallel and non-planar layers. In particular, RBAM can be implemented to realize revolved parts with protruding portions. Cylindrical or conical slicing algorithms have been devised to process the sub-volumes, reducing the number of layers and the need for support structures. In this context, the paper presents a novel algorithm for non-uniform cylindrical slicing that processes sub-volumes connected to a cylindrical shape. The specific contribution of the work is an algorithm that moves from a curved slicing to increase the adhesion between the central body and the first layer, and it relaxes the curvature in the subsequent layers, arriving, if possible, at a planar slicing. The algorithm considers robots’ intrinsic constraints on movements. Planar paths are better approximated than non-planar ones since they prevent the robot from constantly changing the nozzle angle, thus increasing the overall quality of the printing. The algorithm is applied to four test cases and compared with other slicing approaches using numeric indices, objectivating its strengths and limits.

Keywords: Cylindrical slicing | Non-planar slicing | Non-uniform slicing | Robot-based additive manufacturing

Abstract: The 4.0 revolution is leading to increasingly automated, flexible, and intelligent manufacturing systems that require greater complexity to manage during maintenance and process control. In this context the optimization of the human-machine interaction plays a crucial important role in the design of modern industrial systems. Virtual Reality (VR) offers realistic simulation environments where users can be involved to replicate specific human tasks, detecting and solving problems before they occur. The paper proposes a human-centric digital design methodology that integrates VR technologies with human data analysis tools to support the design or redesign of complex industrial systems. Different wearable devices have been used to collect data about physical and mental user conditions to provide an early assessment of the operators’ workload, while comparing different design solutions into the virtual space. An industrial use case related to the redesign of packaging automated machines was used to validate the proposed method and tools: a preliminary correlation between physiological parameters and machines interactions was found.

Keywords: digital simulation | ergonomics and human factors | Human data analysis | Human-centred design | Virtual Reality

Abstract: The Italian ceramic tiles district has a long tradition but is called to face new sustainability challenges related to the profitability, the environmental impact, and the capability to offer pleasant and motivating working conditions for new young employees. New Industry 4.0 approaches are emerging to evolve the current industrial organization and are expected to enhance the overall economic, environmental, and social viability. In this context, this paper aims at demonstrating the positive correlation between the new technologies and the sustainability of the sector. It outlines the main achievements of a 4-year project financed by the Italian government, involving the entire chain made up of research centers, technology providers, and tiles producers. The presented approach is concretized in several technological innovations based on the Industry 4.0 paradigm. Furthermore, a pilot line was created to test the new systems and collect data on the process. The main results are reported in terms of improved sustainability KPIs, such as extended possibility of control of production plants, waste reduction, lower consumption of raw materials and chemical additives. Finally, a sensible increase in the operators’ digitalization level is registered, making a shift from a physical and hard working environment towards more conceptual and attractive job conditions.

Keywords: ceramic tiles | design tools | digital twin | Industry 4.0 | sustainability

Abstract: The objective of this chapter is to describe the strategic action line related to the factories for humans (LI3). In particular, this chapter proposes research and innovation priorities aimed at designing and developing new solutions to enhance the role of human resources and their skills, and contribute to their satisfaction and wellbeing; research and experimentation of new technologies for reducing physical exertion, cooperation with advanced support systems, with collaborative robots and with AI-powered technologies; mapping of knowledge generated on the job, especially implicit knowledge, in a way that is compatible with privacy requirements, introducing advantages both on the human wellbeing front—whether the individuals are users, operators or managers—and in terms of business strategies and procedures. In this regard, innovative factories will need to be increasingly inclusive, strongly geared towards the engagement and participation of individuals (users, operators and managers). These models must take a human-centric approach to look into/investigate new technologies and all the dimensions through which the new factory is defined.

Keywords: Human–machine interaction | Safety and ergonomics | Skills and competences | Training | Workers

Abstract: Earth-moving machine builders require innovative design methods and tool to optimize structural performance while reducing production and design costs, particularly in crucial phases like undercarriage frame design and structural verification. After an in-depth description of the design flow normally followed in industry, the paper presents a computationally efficient method and tool to aid designers in dimensioning extendable tracked undercarriages, aiming to drastically reduce design time and efforts to optimize resources. The proposed tool is based on an analytical model established from in-depth analyses of the undercarriage Computer Aided Design (CAD) assembly and the expertise of the industrial partner. To address the 3D structural problem, a planar system is employed with proper corrective coefficients. These coefficients are meticulously evaluated through direct comparison with Finite Element Method (FEM) models by seamlessly integrating SolidWorks and ANSYS Workbench. The tool accepts as inputs geometric and material data, as well as specific user-defined load scenarios, providing outputs in the form of the deflected configuration of the undercarriage and stress levels. Direct comparison with the results obtained from FEM for three industrial undercarriage models demonstrates the validity of the approach, with errors consistently within the 10% range in almost all cases. This enables designers with no advanced skills in FEM to efficiently validate diverse design variants with minimal effort. Once validated, the tool is integrated with an optimizer in Matlab to conduct computationally efficient design optimization studies. The optimization problem, focused on minimizing the beam’s vertical size while maintaining structural integrity and limiting deflections, has been successfully resolved within a limited computational time, showcasing the benefits of the proposed approach for undercarriage design.

Keywords: CAD/CAE integration | Earth-moving machinery | Engineering design tool | Structural design | Tracked undercarriage

Abstract: Virtual Training (VT) is a recently available modality that uses Virtual Reality (VR) technologies to train people within simulated environments. Companies can use VT to leverage the skills of their staff by avoiding risks related to real production thanks to the digital simulation possibilities and anticipating the training phases to reduce downtime of productive systems [1]. However, the use of VR-based immersive training is still limited in industry due to the cost of equipment and the lack of skilled people able to use VR platforms to effectively implement this type of simulations. This paper deals with the application of low-cost VR equipment to develop virtual training applications. It defines a methodology to create suitable applications for smartphones to be displayed by low-cost, highly portable Google Cardboard. Such equipment could be easily used also by small and medium-sized enterprises (SMEs) that do not have large capitals to invest in traditional VR viewers but are still interested in exploring the adoption of digital tools for training. A case study is presented related to assembly of a 3D printer.

Keywords: Digital Simulation | Ergonomics | Human-centered de-sign | Virtual training | X-reality

Abstract: In the context of Industry 4.0, industrial robots are experiencing wider application fields due to improved capability of executing flexible and diversified manufacturing cycles. The implementation of mechatronic automation systems remains a critical task, since it must cope with many heterogeneous domains, from layout definition to design of mechanical, actuating, and sensing devices, control logic coding, testing and optimization of the whole system. This paper leverages a Python-based connection between a simulation software for robotic cells, i.e. RoboDK, and a PLC system, i.e. Beckhoff TwinCAT, to realize a holistic virtual prototyping environment able to support the design and virtual commissioning of automation systems. The proposed approach is demonstrated with a case study comprising a robotic deburring cell. The resulting application shows the ability to effectively debug logic code, optimize the sequence of manufacturing tasks, and monitor the primary kinematic quantities.

Keywords: RoboDK | Robotic cell | TwinCAT | Virtual Commissioning | Virtual prototyping

Abstract: Position-controlled servomechanisms are the core elements of flexible manufacturing plants, primarily utilized to actuate robotic systems and automated machines. To match specific torque and costs requirements, typical servomechanism arrangements comprise precision reducers, which introduce motion errors that heavily limit the final performance achievable. Such errors are complex to model and depend from speed, dynamic loading conditions and temperature. Accurate characterization is fundamental to develop digital twins and advanced control strategies aimed at their active prediction and compensation. To properly assess the servomechanisms behavior and elaborate high-fidelity virtual models, instrumented test rigs have been proposed which can replicate the time-varying working conditions encountered in real industrial environments. In this context, the present paper reports about a novel engineering method for developing an active loading apparatus, namely a programmable mechatronic device that can deliver custom loads in a highly dynamic manner. The proposed system, consisting of a secondary servomotor and related rotating vector reducer, is integrated and synchronized within an existing instrumented test rig and is controlled in torque mode via a programmable logic controller. The paper mainly focuses on the description of the implemented closed-loop control and on the related tuning and calibration processes, demonstrating that the proposed solutions avoid important measurement errors that could compromise the final effectiveness of the system. The study finally explores the potential benefits of introducing a filter to further enhance system performance. At last, to prove the importance of stabilizing the rig and demonstrate the influence of the control parameters on its measurements, a standard test aimed at assessing the reducer transmission error is conducted adopting different parameter settings.

Keywords: Loading system | Mechanical transmission | Servomechanisms | Stabilization | Test rig | Torque control

Abstract: Robot-based manufacturing cells exhibit strong capability in performing high customizable working cycles involving operations like machining, assembly, painting, welding and gluing. Designing and optimizing such systems require a holistic approach across domains like device layout, logical connections, control systems, and tasks. The AutomationML file format (AML) within the Reference Architectural Model Industrie (RAMI 4.0) framework enhances interconnection and interoperability among engineering tools but lacks established practices. This paper introduces AML for representing flexible manufacturing cells within the Product-Process-Resource paradigm. AML serves as a comprehensive representation of equipment, processed products, and manufacturing operations, aiding design, configuration, virtual simulation, and optimization before physical implementation. A software tool for robotic systems simulation and programming, i.e. RoboDK, is employed to generate customizable virtual prototypes based on AML content for streamlined simulation and assessment. The same AML file facilitates code transfer to physical cell control units. Demonstrated on a robotic deburring cell, this approach highlights AML’s efficacy in data representation between virtual and physical environments, paving the way for digital twin mapping and enhanced manufacturing integration.

Keywords: AutomationML | Interoperability | Offline Programming | RAMI 4.0 | Robotics | Simulation

Abstract: In the modern manufacturing industry, virtual models are normally used in machine and robot design for behavioral analysis and optimization. However, the literature reveals a notable gap in methodologies for simulating and conducting virtual commissioning multi-brand robotic systems with distributed control in a unified software environment before their physical installation. In this context, the present works leverages the open-source robotic libraries within the Robot Operating System (ROS) environment to extend the simulation capabilities of RoboDK software, aiming to support the validation and coordination of complex automated systems. This methodology is validated through procedures for conducting virtual commissioning of a robotic cell for an aircraft fuselage assembly whose process coordinator is defined in ROS. The obtained results demonstrate the effectiveness of the proposed simulation framework.

Keywords: Industrial Robot | RoboDK | ROS | Simulation | Virtual Commissioning

Abstract: Purpose: This paper aims to present a methodology for evaluating the path accuracy of industrial robots using the telescoping ballbar measurement technology. The goal is to improve accuracy assessments in precision-driven manufacturing processes. Design/methodology/approach: A single telescoping ballbar is used to assess the circle contouring performance of a KUKA KR210 R2700 prime robot. Experiments involve system setup, data collection and analysis in Matlab to derive performance metrics such as radial deviation, circularity and path accuracy error. This study investigates the impact of varying the operational conditions, including speed, payload and robot configuration, on these indexes through statistical analysis, and examines the relationship between joint errors and path deviations. Findings: The results indicate that the robot behavior is influenced by the operating conditions, with notable error spikes at joint reversal positions due to factors such as joint backlash and transmission errors. This study evaluates various performance indexes from different standards, ISO 230 and ISO 9283, and identifies key operating parameters influencing each index. The findings suggest effective strategies for error compensation and performance enhancement. Originality/value: This paper offers a novel approach to path accuracy verification and error source identification in industrial robots. It proposes methods to rapidly assess the correlation between performance and operating conditions, offering insights for better calibration and control strategies, especially in high-precision tasks.

Keywords: Backlash | Ballbar | Experimental assessment | Industrial robots | Path accuracy

Abstract: The design of modern production systems is requiring more and more integration of human-in-the-loop principles introduction of new working paradigms, where humans and machines cooperate and interact with each other. Such practices are reinforcing the need for human-centric smart manufacturing (HSM). Today, human-cyber-physical systems (HCPSs) allow to intrinsically meet the industrial complexity and bring insights in the development and implementation of HSM. In this context, the growing interest of academics and practitioners on the three key concepts of “sustainability, human-centric, and resiliency” related to the Industry 5.0 (I5.0) framework is justified. The aim of this study is to present a methodological approach for the design of adaptive human-cyber-physical systems to meet the I5.0 objectives. Starting from the analysis of the as-is user and process-related conditions, this innovative closed-loop framework guarantees a step-by-step tuning logic according to specified objectives. A use case concerning a quality control procedure for the Oil&Gas sector is proposed, where a preliminary HCPS prototype has been developed and tested. The solution provides a contextual support throughout all the value chain to the diverse activities carried out by design engineers up to end-users by offering a valuable operator’s user experience (UX). The main results suggested that the conceived strategy overcomes traditional limitations of the technical drawings by integrating model-based engineering with human-centred design (HCD) principles. The systematic introduction of HCPS allows to redesign the human–machine interaction according to new paradigms of collaboration between the humans and the smart factory.

Keywords: Augmented reality | Human-cyber-physical system | Human-in-the-loop | Human-machine interaction | Industry 5.0

Abstract: [No abstract available]

Abstract: The concept of Industry 5.0 (I5.0) promotes the human-centricity as the core value behind the evolution of smart manufacturing systems (SMSs), based on a novel use of digital technologies in the design and management of modern industrial systems to take up the socio-technical challenges. In this context, the paper proposes a Smart Manufacturing Systems Design (SMSD) framework enabling I5.0, based on the human-automation symbiosis. Thanks to an ‘Augmented Digital Twin’ (ADT) able to integrate and digitize all the entities of the factory (i.e. machines, robots, environments, interfaces, people), AI-driven applications can be built to support the user domain and make people and machines co-evolve thanks to a systematic data sharing between physical and digital assets (e.g. digital twin, virtual mock-ups, human-machine interfaces), optimizing factory productivity and workers wellbeing. In this framework, machines and humans can both generate knowledge and learn from each other, generating a virtuous co-evolution, supporting the understanding of the human-machine interplay and the creation of an effective collaboration between people and SMSs. The framework was conceived and validated involving four industrial companies, belonging to diverse sectors, interested in overcoming the current limits of I4.0 lines by including the human factors for future SMS management.

Keywords: augmented digital twin | human-automation symbiosis | Industry 5.0 | Operator 4.0 | Operator 5.0 | smart manufacturing systems

Abstract: Industrial Robots (IRs) are increasingly adopted for material subtraction or deposition functions owing to their advantages over machine tools, like cost-effectiveness and versatility. Unfortunately, the development of efficient robot manufacturing processes still faces unsolved issues related to the IRs poor positioning accuracy and to the tool path generation process. Novel engineering methods and tools are needed for CAD based programming of accurate paths and continuous robot motions to obtain the required manufacturing quality and tolerances. Within this context, to achieve smoothness along the tool path formed by linear G-code segments, the IR controllers’ approximation strategies, summarily reported in the manufacturer’s manuals, must be considered. The aim of this paper is to present the preliminary work carried out to identify the approximation algorithms of a Kuka IR when executing linear moves. An experimental study is conducted by varying the controller settings and the maximum translational velocity. The robot behavior has been acquired thanks to the controller tracing function and then processed to yield relations readily employable for the interpretation of G-Code commands and the subsequent generation of proper robot motion instructions. The obtained formulas allow to accurately predict the robot geometric path and kinematics within the corner transition between two linear segments.

Keywords: Corner smoothing | G-code translation | Manufacturing robots | Path approximation | Robot programming

Abstract: Nowadays, manufacturing plants are required to be flexible to respond quickly to customer demands, adapting production and processes without affecting their efficiency. In this context, Industrial Robots (IRs) are a primary resource for modern factories due to their versatility which allows the execution of flexible, reconfigurable, and zero-defect manufacturing tasks. Even so, the control and programming of the commercially available IRs are limiting factors for their effective implementation, especially for dynamic production environments or when complex applications are required. These issues have stimulated the development of new technologies that support more efficient methods for robot control and programming. The goal of this research is to identify and evaluate the main approaches proposed in scientific papers and by the robotics industry in the last decades. After a critical review of the standard IR control schematic, the paper discusses the available control alternatives and summarizes their characteristics, range of applications, and remaining limitations.

Keywords: industrial robots | instruction streaming | open controller | robot control | robot programming | trajectory streaming

Abstract: Robot-Based Additive Manufacturing (RBAM) combines material deposition nozzles and robotic manipulators to increase the flexibility of cartesian/delta Additive Manufacturing (AM) systems. RBAM overcomes the traditional limit given by the planarity of the manufacturing layer and allows variable slice thickness to be realized. Also, RBAM enables the deposition of the material in multiple directions. In this context, volume decomposition algorithms are implemented to split a solid into several sub-volumes. Each sub-volume is sliced according to an optimal direction to perform support-free manufacturing and to avoid tool collisions. A novel algorithm for the volume decomposition of a given input geometry is presented. In particular, it allows several planar separation surfaces to be computed that are used to split a general input shape. The surfaces are defined by analyzing overhangs according to an initial slicing direction. The normal of the surfaces identifies the slicing direction of the related sub-volumes. The algorithm steps are iterated to reach the complete removal of overhangs. The approach is tested in some case studies to evaluate its applicability.

Keywords: Additive Manufacturing | Multi-Slicing Direction | Robot-based Additive Manufacturing | Volume decomposition

Abstract: The importance of training for operators in industrial contexts is widely highlighted in literature. Virtual Reality (VR) is considered an efficient solution for training, since it provides immersive, realistic, and interactive simulations environments promoting a learn-by-doing approach, far from the risks of the real field. Its efficacy has been demonstrated by several studies, but a proper assessment of the operator’s cognitive response in terms of stress and cognitive load during the use of such technology is still lacking. This paper proposes an integrated methodology for the analysis of user’s cognitive states, suitable for each kind of training in the industrial sector and beyond, fostering the human-centred design and manufacturing perspective. The methodology has been assessed using an industrial case study where virtual training is used for assembly of agricultural vehicles. Experimental results highlighted that, with VR additional supportive information, while operators’ errors drastically decrease, the stress increases for complex tasks, due to the greater amount of information to manage. The proposed protocol allows understanding the operators’ cognitive conditions in order to optimize the VR training application, avoiding operators’ stress, mental overload, and improving performance.

Keywords: cognitive ergonomics | mental workload | stress | virtual assembly | Virtual reality | virtual training

Abstract: In recent decades industrial development has led to increasingly sophisticated machinery and systems, which require complex maintenance routines. Consequently, maintenance operators may not have the sufficient skills to perform recovery procedures properly and quickly, so that the need of assistance from the manufacturer's after-sales service or companies specialized in maintenance services. Such actions usually lead to very long recovery times, high maintenance costs, and a temporary drop in production. In this scenario, we should consider that Industry 4.0 is making available innovative technologies, such as Augmented Reality (AR), suitable for improving the skills and competencies of operators without burdening their cognitive load, and consequently wellbeing. However, technologies must be selected, designed, and used according to the users' needs to be effective and useful. The paper presents a user experience (UX)-driven methodology for designing user-centric AR applications for complex maintenance procedures. The methodology was applied to a real industrial case concerning the management of CNC machines in a plant producing tractors components, where a smartphone-based AR application was designed and tested with users. The satisfactory results highlighted the potential benefits of AR in industry and specifically in maintenance.

Keywords: Augmented Reality | Industry 4.0 | Maintenance | Operator 4.0 | User experience design

Abstract: The Servo-Mechanisms (SMs) mounted in industrial robots joints are a major source of positioning accuracy errors. To improve robots precision performance, researchers have been focusing on the development of novel SMs design and control strategies, which need extensive experimental analyses to tune their parameters. In this context, the scope of this paper is double: first, to present the novel experimental apparatus and methods designed to improve the accuracy of the transmission performance evaluation of high dynamics SMs and, secondly, to report and discuss the achieved experimental results. In the first part, a description of the test rig tuning operations is given, primarily focusing on the signals synchronization and on the elimination of the measuring errors caused by the mechanical transmission elasticity and the servomotor torque ripples. Then, control strategies for compensating the torque ripples and input speed errors are defined. It is shown that speed oscillations can be reduced of ≈70% when rotating the servomotor up to 2000 rpm, improving the measurement quality of the reducer performance. In the second part, a set of experiments is carried out to assess the combined effect of input speed and lubricant temperature on the reducer behavior. The system sensitivity to the variation of the input parameters is confirmed by the dynamic lost motion curves, whose mean value equals 16.8″ and 35.4″ when the reducer is operated at its minimum and maximum friction load respectively. At last, the extrapolated harmonic content is used to build a simple mathematical model of the reducer transmission error.

Keywords: Experimental methods | Lubricant temperature | Robot reducers | Servo-mechanisms | Test rig | Torque ripples | Transmission error

Abstract: The European Commission defined the new concept of Industry 5.0 meaning a more human-centric, resilient, and sustainable approach for the design of industrial systems and operations. A deep understanding of the work environment and organization is important to start analysing the working conditions and the resulting User eXperience (UX) of the operators. Also, the knowledge about users’ needs and ergonomics is fundamental to optimize the workers’ wellbeing, working conditions, and industrial results. In this context, the paper presents a strategy to effectively assess the UX of workers to promote human-centric vision of manufacturing sites, enhancing the overall sustainability of the modern factories. A set of non-invasive wearable devices is used to monitor human activities and collect physiological parameters, as well as questionnaires to gather subjective self-assessment. This set-up was applied to virtual reality (VR) simulation, replicating heavy duty work sequence tasks that took place in an oil and gas pipes manufacturing site. This approach allowed the identification of possible stressful conditions for the operator, from physical and mental perspectives, which may compromise the performance. This research was funded by the European Community's HORIZON 2020 programme under grant agreement No. 958303 (PENELOPE).

Keywords: Cognitive ergonomics | Human-centred design | Industry 5.0 | User experience | Virtual reality

Abstract: Intelligent robotic manufacturing cells must adapt to ever-varying operating conditions, developing autonomously optimal manufacturing strategies to achieve the best quality and overall productivity. Intelligent and cognitive behaviors are realized by using distributed controllers, in which complex control logics must interact and process a wide variety of input/output signals. In particular, programmable logic controllers (PLCs) and robot controllers must be coordinated and integrated. Then, there is the need to simulate the robotic cells’ behavior for performance verification and optimization by evaluating the effects of both PLC and robot control codes. In this context, this work proposes a method, and its implementation into an integrated tool, to exploit the potential of ABB RobotStudio software as a virtual prototyping platform for robotic cells, in which real robots control codes are executed on a virtual controller and integrated with Beckhoff PLC environment. For this purpose, a PLC Smart Component was conceived as an extension of RobotStudio functionalities to exchange signals with a TwinCAT instance. The new module allows the virtual commissioning of a complete robotic cell to be performed, assessing the control logics effects on the overall productivity. The solution is demonstrated on a robotic assembly cell, showing its feasibility and effectiveness in optimizing the final performance.

Keywords: robotic cell | RobotStudio | TwinCAT | virtual commissioning | virtual prototyping

Abstract: Compared to other additive technologies, Wire and Arc Additive Manufacturing (WAAM) offers high deposition rates, flexibility and a larger build volume as well as reduction of material waste. WAAM can be combined with a subtractive technology in hybrid robotic cells to further increase the application scope, thus producing products with improved surface finish where needed. However, there are some open issues that limit this process. So, the main goal of this paper is to review current research developments and provide a framework aimed at manufacturing parts by hybrid cells. A procedure is defined which moves from the evaluation of the designed shapes, their analysis to identify a proper manufacturing sequence until the elaboration of the instructions for the cell automaton controllers. Main WAAM issues are outlined to identify main research directions, and a test case is presented to highlight the process phases.

Keywords: Hybrid manufacturing | Process planning | Robotic cell | Wire and arc additive manufacturing

Abstract: The fourth industrial revolution is evolving the machines as well as the abilities of people working in the factories. Human roles and tasks are changing, moving from highly physical tasks to decision-making and high-precision activities, asking for different competencies and creating new types of interactions with machines. This paper reviews the design and engineering methods for the inclusion of human factors in modern companies. Human factor integration (HFI) can play a key role in the design of factories with a great impact on social aspects and global process sustainability. The paper proposes a systematic view of the main tools to design human-centered industrial processes, with a specific focus on manufacturing, and discusses trends to achieve and effective HFI.

Keywords: Engineering methods | Ergonomics | Human factors | Human-centered design

Abstract: The fourth industrial revolution is characterized by flexible production systems that can respond to the demand for high variability and customization of the product. To maintain the efficiency of the production process, automated and flexible solutions are mandatory. This paper describes an approach to design Virtual Prototypes of robotic cells and support designer in the definition and simulation of the manufacturing system. The identified model is capable of replicating the performance of the cell under different aspects in a holistic manner: geometry, operating logic, performance, and physical behavior. The design approach is demonstrated on a robotic cell composed of two anthropomorphic robots for the flexible process of automatic assembly of mechanical parts. The resulting model proves to be straightforward, accurate and complete.

Keywords: Digital Twin | Physics-based simulation | Robotic assembly | Virtual Prototype

Abstract: Designing highly usable and ergonomic dashboards is fundamental to support users in managing and properly setting complex vehicles, like trains, airplanes, trucks and tractors. Contrarily, control dashboards are usually intrusive, full of controls and not really intuitive or usable. This paper focuses on the design of ergonomic and usable dashboard for specific classes of vehicles, like tractors and trucks. Indeed, trucks and tractors are both vehicles and operating machines, and their control is particularly complex. Indeed, the driver contemporary drives and checks if the machine is working properly. The paper proposes an innovative methodology to design highly usable and compact dashboards inspired by human-centered design and ergonomics principles. The study started by shifting the attention from the machine performance, that is the conventional engineering approach, to the human-system interaction quality, according to a new, transdisciplinary approach. The methodology proposes to combine virtual simulations with human performance analysis to support the design at different stages, from concept generation to detailed design, until testing with users. The methodology uses virtual environments to create digital twins of both driver and controls, making users interact with virtual items and predict the type and nature of interaction. Within virtual scenarios, different configurations of dashboard controls can be easily compared and tested, checking the frequency of use of each control and measuring the achieved human performance related to postural comfort and mental workload. The study adopted the proposed methodology to two industrial use cases focusing on the design of ergonomic dashboards: the former is referred to tractor dashboard and armrest, the latter refers to truck dashboard and seat. Both cases demonstrated that the new methodology allowed improved comfort, higher usability, higher visibility and accessibility, better performance and reduced time for machine control. The study demonstrates how a multidisciplinary user information integration can drive design optimization.

Keywords: Ergonomics | Human factors | Human-centered design | Usability | Virtual simulation

Abstract: Successful interaction with complex processes, like those in the modern factory, is based on the system’s ability to satisfy the user needs during human tasks, mainly related to performances, physical comfort, usability, accessibility, visibility, and mental workload. However, the ‘real’ user perception is hidden and usually difficult to detect. User eXperience (UX) is a useful concept related to subjective perceptions and responses that result from the interaction with a product, system or process, including users’ emotions, beliefs, preferences, perceptions, physical and psychological responses, behaviors and accomplishments that occur before, during and after use. The paper proposes the creation of a User eXperience Index (UXI) to assess the quality of human-system interaction during job tasks and, consequently, evaluate both process and workstation. The proposed approach has been applied to improve the design of assembly human tasks, using a virtual simulated case study focusing on tractor assembly. Tests with users, with different levels of expertise, allowed us to validate the proposed approach and to optimize the assembly task sequence. Results showed how the proposed UXI can validly objectify the workers’ experience and can be validly used to improve the design of human tasks.

Keywords: ergonomics | human factors engineering | human monitoring | Human-centered design | transdisciplinary engineering | user experience | virtual assembly

Abstract: Industry 4.0 is driving the revolution of manufacturing processes by combining innovative technologies and new interaction paradigms among systems and operators. In particular, the layout, tasks and work sequences of assembly lines are designed according to several transdisciplinary Design Principles (DPs), such as process efficiency, product quality, ergonomics, safety and operators' workload. A large variety of simulation software can be employed for evaluations. However, the related ability to assess multidisciplinary factors must be evaluated. The paper aims to provide a framework for guiding the assessment of simulation software in the context of Industry 4.0 assembly lines. Process requirements are first analyzed and mapped to select DPs, prioritized according to design goals by an analytical hierarchy process. Then, suitable simulation software is determined accordingly, and the virtual model is realized. Finally, the possibility of the software to provide meaningful elaborations for the selected DPs is assessed. The framework has been tested on a prototypal Industry 4.0 assembly line composed of automated logistic systems, cobots and systems to guide the execution of tasks. The line has been modeled in Siemens Process Simulate, analyzing the completeness and appropriateness of the functionalities of this software according to the defined DPs.

Keywords: Decision Support Tools | Design Principles | Industry 4.0 | Interactive Simulation for Engineering | Transdisciplinary Engineering

Abstract: Understanding user experience (UX) is essential to design engaging and attractive products, so nowadays has emerged an increasingly interest in user-centred design approach; in this perspective, digital technologies such as Virtual Reality (VR) and Mixed Reality (MR) could help designers and engineers to create a digital prototype through which the user feedback can be considered during the product design stage. This research aims at creating an interactive Digital Twin (DT) using MR to enable a tractor driving simulation and involve real users to carry out an early UX evaluation, with the scope to validate the design of the control dashboard through a transdisciplinary approach. MR combines virtual simulation with real physical hardware devices which the user can interact with and have control through both visual and tactile feedback. The result is a MR simulator that combines virtual contents and physical controls, capable of reproducing a plowing activity close to reality. The principles of UX design was applied to this research for a continuous and dynamic UX evaluation during the project development.

Keywords: Digital Engineering | Digital Twin | Human-centered Design | Mixed Reality | User experience design

Abstract: Human factors integration is definitely a transdisciplinary and urgent matter in modern factories. Despite the great surge in factory automation in recent years, human-machine interaction is still a crucial aspect and companies need to take care of the workers' wellbeing and performance to enhance the overall system quality and productivity. Nevertheless, ergonomics is poorly considered during the design of complex industrial systems, such as automatic machinery, especially for the lack of practical methodologies and guidelines to promote human factors from the early stages of design or redesign. To overcome this issue, this work proposes a transdisciplinary approach to redesign automatic machinery in compliance with factory ergonomics, using a combination of digital technologies (e.g., digital human simulation, human physiological data monitoring). The paper defines a structure method and related tools to apply a human-centric approach to industrial cases and their validation of a real case, concerning the redesign of a packaging automatic machine. Results show how the proposed approach is useful to detect possible ergonomic issues at the shop floor, identifying in advance risky situations for the operators during operating or maintenance tasks, and leading to an optimized machine able to enhance the workers' wellbeing and factory productivity at the same time.

Keywords: digital human simulation | ergonomics | human factors integration | human monitoring | human-centered design

Abstract: In the last decade, the field of Human-Robot Collaboration (HRC) has received much attention from both research institutions and industries. Robot technologies are in fact deployed in many different areas (e.g., industrial processes, people assistance) to support an effective collaboration between humans and robots. In this transdisciplinary context, User eXperience (UX) has inevitably to be considered to achieve an effective HRC, namely to allow the robots to better respond to the users' needs and thus improve the interaction quality. The present paper reviews the evaluation scales used in HRC scenarios, focusing on the application context and evaluated aspects. In particular, a systematic review was conducted based on the following questions: (RQ1) which evaluation scales are adopted within the HRI scenario with collaborative tasks?, and (RQ2) how the UX and user satisfaction are assessed?. The records analysis highlighted that the UX aspects are not sufficiently examined in the current HRC design practice, particularly in the industrial field. This is most likely due to a lack of standardized scales. To respond to this recognized need, a set of dimensions to be considered in a new UX evaluation scale were proposed.

Keywords: Human-Robot Collaboration | Review | Transdisciplinary engineering | User experience evaluation | User experience scale

Abstract: Nowadays, robot-based additive manufacturing (RBAM) is emerging as a potential solution to increase manufacturing flexibility. Such technology allows to change the orientation of the material deposition unit during printing, making it possible to fabricate complex parts with optimized material distribution. In this context, the representation of parts geometries and their subsequent processing become aspects of primary importance. In particular, part orientation, multiaxial deposition, slicing, and infill strategies must be properly evaluated so as to obtain satisfactory outputs and avoid printing failures. Some advanced features can be found in commercial slicing software (e.g., adaptive slicing, advanced path strategies, and non-planar slicing), although the procedure may result excessively constrained due to the limited number of available options. Several approaches and algorithms have been proposed for each phase and their combination must be determined accurately to achieve the best results. This paper reviews the state-of-the-art works addressing the primary methods for the representation of geometries and the subsequent geometry processing for RBAM. For each category, tools and software found in the literature and commercially available are discussed. Comparison tables are then reported to assist in the selection of the most appropriate approaches. The presented review can be helpful for designers, researchers and practitioners to identify possible future directions and open issues.

Keywords: Geometry processing | Multiaxial deposition | Robot-based additive manufacturing | Slicing strategy | Volume decomposition

Abstract: Recent advances in physiological monitoring devices have supported the diffusion of a human-centric approach also within industrial contexts, where often severe working conditions limit the analysis of the operators' User eXperience (UX). Several methodologies have been presented to the scientific community to assess the overall UX of workers performing industrial operations. These methodologies have also tried to encompass the diverse aspects of the physiological response (e.g., mental workload, stress conditions and postural overloads). The current study aims to refine a unique and comprehensive UX index to identify the specific causes of the user discomfort in advance and to optimize the overall system design. A full set of non-invasive wearable devices was applied to a virtual reality (VR) simulation while performing manual operations to collect relevant physiological parameters and to finally assess the overall UX. The results demonstrated the effectiveness of the proposed index in anticipating the operator's critical conditions by specifying the possible causes of the ergonomic discomfort. Future works will focus on investigating the theoretical foundation of proposed solution and on providing a statistical validation on a larger population.

Keywords: Ergonomic Index | Human Monitoring | Human-Centered Design | Industry 5.0 | User Experience | Virtual Reality

Abstract: The human‐centered design (HCD) approach places humans at the center of design in order to improve both products and processes, and to give users an effective, efficient and satisfy-ing interactive experience. In industrial design and engineering, HCD is very useful in helping to achieve the novel Industry 5.0 concept, based on improving workers’ wellbeing by providing prosperity beyond jobs and growth, while respecting the production limits of the planet as recently promoted by the European Commission. In this context, the paper proposes an ergonomic assessment method based on the analysis of the workers’ workload to support the design of industrial products and processes. This allows the simultaneous analysis of the physical and cognitive workload of operators while performing their tasks during their shift. The method uses a minimum set of non‐invasive wearable devices to monitor human activity and physiological parameters, in addition to questionnaires for subjective self‐assessment. The method has been preliminarily tested on a real industrial case in order to demonstrate how it can help companies to support the design of optimized products and processes promoting the workers’ wellbeing.

Keywords: Design for ergonomics | Human factors | Human‐centered design | Product design | Workload assessment

Abstract: The fourth industrial revolution is promoting the Operator 4.0 paradigm, originating from a renovated attention towards human factors, growingly involved in the design of modern, human-centered processes. New technologies, such as augmented reality or collaborative robotics are thus increasingly studied and progressively applied to solve the modern operators’ needs. Human-centered design approaches can help to identify user’s needs and functional requirements, solving usability issues, or reducing cognitive or physical stress. The paper reviews the recent literature on augmented reality-supported collaborative robotics from a human-centered perspective. To this end, the study analyzed 21 papers selected after a quality assessment procedure and remarks the poor adoption of user-centered approaches and methodologies to drive the development of human-centered augmented reality applications to promote an efficient collaboration between humans and robots. To remedy this deficiency, the paper ultimately proposes a structured framework driven by User eXperience approaches to design augmented reality interfaces by encompassing previous research works. Future developments are discussed, stimulating fruitful reflections and a decisive standardization process.

Keywords: Augmented reality | Human factors | Human-centered design | Human–robot collaboration | Human–robot interaction | User eXperience

Abstract: Nowadays companies have to face a competitive market that requires small volumes with a high level of customisations. In this context, assembly quality and timeliness is crucial. To guarantee flexibility and personalization, manual operations still have a crucial role for a lot of manufacturing sectors, so that workers' conditions and ergonomics are important factors to achieve a better product quality and overall cost reduction. Ergonomics evaluation in manufacturing is a challenging and expensive activity that requires a transdisciplinary approach, to merge technical and social sciences to finally have a consolidated and reliable evaluation. This paper compared two digital human simulations tools offered by Siemens Tecnomatix: Jack and Process Simulate. They were applied on the same industrial case study, concerning the hood assembly of an agricultural machine, comparing results on ergonomics reports and usage time. Results confirmed the advantage of adopting a digital approach to predict the human effort and ergonomic risk related to a series of tasks. At the same time, they showed the major strengths and weaknesses of the two analysed tools and defined how they can be successfully adopted by companies. The paper finally provided guidelines to drive companies in choosing the best tool according to their needs.

Keywords: Digital human simulations | Digital manufacturing | Ergonomics | Human-centered design | Transdisciplinary engineering

Abstract: Virtual reality (VR) offers a promising set of technologies to digitally simulate industrial processes and interaction between humans and machines. However, the use of immersive VR simulations is still limited in industry due to the uncertainty of benefits in respect with traditional digital tools, and the lack of structured methodologies to effectively implement immersive virtual simulations in practice. This paper deals with the application of VR to create virtual manufacturing simulations with the aim to design assembly lines in compliance with factory ergonomics. It proposes a methodology to allow the virtualization and simulation of assembly tasks using a combination of VR tools by replicating, or rather anticipating, what would happen at the shop floor. The adopted tools are Unity 3D for virtual environment generation, HTC VIVE to immerse the user in the virtual factory layout, Xsens as tracking system, and Leap Motion for gesture recognition. The paper also compares the new VR-based procedure with a more traditional desktop-based digital simulation on industrial cases. Results show that the new methodology is more precise to detect the operator’s comfort angles and more powerful to predict process criticalities and optimize factory layout design. At the same time, it is less sensitive to errors during ergonomic assessment related to the expert’s subjectivity during the analysis.

Keywords: Human-centered design | Industrial ergonomics | Virtual manufacturing | Virtual reality

Abstract: In recent years Human-Robot Collaboration (HRC) has become a strategic research field, considering the emergent need for common collaborative execution of manufacturing tasks, shared between humans and robots within the modern factories. However, the majority of the research focuses on the technological aspects and enabling technologies, mainly directing to the robotic side, and usually neglecting the human factors. This work deals with including the needs of the humans interacting with robots in the design in human-robot interaction (HRI). In particular, the paper proposes a user experience (UX)-oriented structured method to investigate the human-robot dialogue to map the interaction with robots during the execution of shared tasks, and to finally elicit the requirements for the design of valuable HRI. The research adopted the proposed method to an industrial case focused on assembly operations supported by collaborative robots and AGVs (Automated Guided Vehicles). A multidisciplinary team was created to map the HRI for the specific case with the final aim to define the requirements for the design of the system interfaces. The novelty of the proposed approach is the inclusion of typically interaction design tools focusing in the analysis of the UX into the design of the system components, without merely focusing on the technological issues. Experimental results highlighted the validity of the proposed method to identify the interaction needs and to drive the interface design.

Keywords: Human Factors | Human-Robot Collaboration | Human-Robot Interaction | Industrial Ergonomics | User eXperience

Abstract: The optimization of the energy consumption of Industrial Robots (IRs) has been widely investigated. Unfortunately, on the field, the prediction and optimization strategies of IRs energy consumption still lack robustness and accuracy, due to the elevated number of parameters involved and their sensitivity to environmental working conditions. The purpose of this paper is to present, and share with the research community, an extensive experimental campaign that can be useful to validate virtual prototypes computing the energy consumption of robotic cells. The test cell, comprising a high payload IR equipped with multiple sensors and different payloads, is firstly described. The testing procedures are then presented. Experimental results are analyzed providing novel qualitative and quantitative evaluations on the contribution and relevance of different power losses and system operating conditions, clearly depicting the nonlinear relation between the energy consumption and various freely programmable parameters, thus paving the way to optimization strategies. Finally, all the experimental tests data are provided in the form of an open research dataset, along with custom Matlab scripts for plotting graphs and maps presented in this paper. These tests, which are verifiable via the shared dataset, consider the overall measured IR energy consumption (as drawn from the electric network) and highlight that, in some industrially interesting case scenarios, optimization potentials for energy savings of more than 50% are possible.

Keywords: Energy optimization | Experimental campaign | Industrial robotics | Industry 4.0 | Sustainable manufacturing

Abstract: Product and process digitalization is pervading numerous areas in the industry to improve quality and reduce costs. In particular, digital models enable virtual simulations to predict product and process performances, as well as to generate digital contents to improve the general workflow. Digital models can also contain additional contents (e.g., model-based design (MBD)) to provide online and on-time information about process operations and management, as well as to support operator activities. The recent developments in augmented reality (AR) offer new specific interfaces to promote the great diffusion of digital contents into industrial processes, thanks to flexible and robust applications, as well as cost-effective devices. However, the impact of AR applications on sustainability is still poorly explored in research. In this direction, this paper proposed an innovative approach to exploit MBD and introduce AR interfaces in the industry to support human intensive processes. Indeed, in those processes, the human contribution is still crucial to guaranteeing the expected product quality (e.g., quality inspection). The paper also analyzed how this new concept can benefit sustainability and define a set of metrics to assess the positive impact on sustainability, focusing on social aspects.

Keywords: Augmented reality | Humancentered design | Model-based design | Product development | Quality inspection | Social sustainability

Abstract: Additive Manufacturing (AM) technologies have expanded the possibility of producing unconventional geometries, also increasing the freedom of design. However, in the designer’s everyday work, the decision regarding the adoption of AM for the production of a component is not straightforward. In fact, it is necessary to process much information regarding multiple fields to exploit the maximum potential of additive production. For example, there is a need to evaluate the properties of the printable materials, their compatibility with the specific application, redesign shapes accordingly to AM limits, and conceive unique and complex products. Additionally, procurement and logistics evaluations, as well as overall costs possibly extending to the entire life cycle, are necessary to come to a decision for a new and radical solution. In this context, this paper investigates the complex set of information involved in this process. Indeed, it proposes a framework to support and guide a designer by means of a structured and algorithmic procedure to evaluate the opportunity for the adoption of AM and come to an optimal design. A case study related to an ultralight aircraft part is reported to demonstrate the proposed decision process.

Keywords: Additive manufacturing | Design for additive manufacturing | Multi criteria decision‐making | Product design

Abstract: Servo-Actuated Mechanisms (SAM) are capable of improving the flexibility and reconfigurability of modern automatic machines. On one hand, as compared to fully mechanical drives, SAM may suffer from non-negligible positioning inaccuracies, whose effect can become unacceptable in case of undesired part deformations during high dynamic motions. On the other hand, it may be the case that parts of the system are purposely designed to provide an highly compliant behaviour, so as to potentially increase the device safety in case of interaction with humans. In both cases, practical strategies to reduce the SAM positioning errors are necessary. As a possible solution to such issue, in this paper, an integrated approach to improve the accuracy of a partially compliant SAM in position-controlled tasks is described. The method exploits a multi-software framework comprising Matlab and RecurDyn, namely a commercial Computer-Aided Engineering (CAE) tool that can be used to simulate the motion of systems comprising both rigid and flexible bodies. Starting from an initial, sub-optimal, motion law of the input link, a trajectory optimizer iteratively runs the CAE solver and automatically computes an optimal, compensated, position profile. The obtained results show that the method may represent a useful tool for analyzing/designing partially compliant SAM, whenever analytical models are either too complex or not readily available.

Abstract: Virtual reality (VR) training allows companies to train their workforce thanks to virtually simulated environments, leveraging the skills of people before the system production with the final aim to reduce the downtime of productive equipment and improve the global factory efficiency. However, the use of VR immersive training is still limited in industry due to the lack of structured methodologies to effectively implement these simulations. This paper deals with the application of VR technologies to create virtual training simulations addressing assembly or maintenance tasks. It suggests a methodology to create an interactive virtual space in which operators can perform predefined tasks in a realistic way, having dedicated instructions to support the learn-by-doing, based on key training features (KTFs). This methodology was applied to an industrial case study concerning some specific tractor assembly phases. Results show that operators generally appreciate this new training process, enabling faster and more intuitive learning.

Keywords: Smart factory | Virtual assembly | Virtual factory | Virtual reality | Virtual training

Abstract: The importance of training for operators in industrial contexts is widely highlighted in literature. Virtual Reality (VR) technology is considered an efficient solution for training, since it provides immersive, realistic, and interactive simulations environments where the operator can learn-by-doing, far from the risks of the real field. Its efficacy has been demonstrated by several studies, but a proper assessment of the operator's cognitive response in terms of stress and cognitive load, during the use of such technology, is still lacking. This paper proposes a comprehensive methodology for the analysis of user's cognitive states, suitable for each kind of training in the industrial sector and beyond. Preliminary feasibility analysis refers to virtual training for assembly of agricultural vehicles. The proposed protocol analysis allowed understanding the operators' loads to optimize the VR training application, considering the mental demand during the training, and thus avoiding stress, mental overload, improving the user performance.

Keywords: Cognitive ergonomics | Industrial ergonomics | Training Assessment | Virtual assembly | Virtual Reality

Abstract: The Industry 4.0 framework is pushing the manufacturing systems towards a zero-defect production based on robot technologies. The increasing level of automation in the production lines is raising new challenges for designers that must face the latest requirements in terms of product quality and power consumption. Among the multitude of components of the industrial plants, Servo-Mechanisms (SMs) play a crucial role and govern important performance indices of both robots and automatic machines. During the execution of high dynamics tasks, the SMs performance is influenced by many factors, including motion law, acting load, temperature and degradation. The development of accurate models aiming at predicting and optimizing the SMs behavior may not be practicable without extensive experimental activities. Owing to these considerations, this work introduces a novel test rig for the accurate characterization of industrial SMs. The rig is designed by combining the advantages of the existing prototypes. It is equipped with high precision sensors and an active loading system that enable to test the SM in various working conditions. Also, the rig modularity facilitates the installation of newly commissioned components and the execution of static and dynamic experiments. The paper mainly focuses on the rig mechanical design and components selection criteria.

Keywords: Computer Aided Design | Design methods | High Precision Manufacturing | Industry 4.0 | Servo-Mechanism Test Rig

Abstract: Latest trends and developments in digital technologies have enabled a new manufacturing model. Digital systems can monitor, optimize and control processes by creating a virtual copy of the physical world and making decentralized decisions. This paradigm relies on the development of a digital counterpart, the Digital Twin, for each production resource taking part to the whole manufacturing process. Although real applications of Digital Twin may differ in technical and operational details, in the past years, a huge effort has been done in order to identify and define focal functionalities and properties, as well as main challenges for the practical implementation within real factories. This paper is intended to review and analyse principles, ideas and technological solutions of the Digital Twin vision for production processes focusing on the practical industrial implementation. The purpose of this document is therefore to summarize the current state-of-art on Digital Twin concepts, and to draw their up-to-date state for application and deployment in real industrial processes. Finally, future directions for further research are discussed.

Keywords: Digital twin | digital twin industrial architecture | industrial implementation | industry 4.0 | smart manufacturing

Abstract: Robot geometrical calibration aims at reducing the global positioning accuracy of a robotic arm by correcting the theoretical values of the kinematic parameters. A novel method for the geometrical calibration of robotic arms used in industrial applications is proposed. The proposed approach mainly focuses on the final positional accuracy of the robotic tool center point (TCP) when executing an industrial task rather than on the accurate estimation of the kinematic parameters themselves, as done so far by many calibration methods widely discussed in literature. A real industrial use-case is presented, and the steps of the proposed calibration procedure for the robotic arm are described. Experimental methodology and results for the identification of geometrical parameters are also discussed. A practical validation of the final positional accuracy of the robotic arm (after kinematic calibration) was performed, and experimental results validated the proposed procedure, proving its feasibility and effectiveness in the considered industrial scenario.

Keywords: Aircraft assembly | Kinematic calibration | Laser tracker | Non-linear least square solver | Positional accuracy | Process capability indexes

Abstract: Designing highly usable and ergonomic control dashboards is fundamental to support the user in managing and properly setting complex machines, like trains, airplanes, trucks and tractors. Contrarily, control dashboards are usually big, intrusive, full of controls and not really usable for different users. This paper focuses on the re-design of an ergonomic and compact dashboard for tractor control, proposing an innovative methodology in line with human-centered design and ergonomics principles. The study started by shifting the focus from how a machine works to how a task has to be performed and how the user interacts with the machine. It uses virtual simulations and human performance analysis tools to support the concept generation and the detailed design, and to test the new idea with users in the virtual lab. Indeed, within the virtual environment, different configurations of controls can be tested, checking which controls are mostly used and measuring human performance indexes (i.e., postural comfort and mental workload) for each configuration. Virtual mannequins can be used to as "digital twins"to interact with virtual items and to calculate robust comfort indicators during task execution. The study adopted the proposed methodology to an industrial use case to develop a usable and compact armrest for a new tractor platform. The new armrest is smaller than the previous one (-30% in dimensions), more usable (keeping on board only frequent controls, better positioned), and more comfortable (it satisfies 95% of the population size). This new approach could be used also for the design of new products.

Keywords: Human Factors | Human-centered design | Usability | Virtual simulation

Abstract: Successful interaction with complex systems is based on the system ability to satisfy the user needs during interaction tasks, mainly related to performances, physical comfort, usability, accessibility, visibility, and mental workload. However, the "real"user experience (UX) is hidden and usually difficult to detect. The paper proposes a Transdisciplinary Assessment Matrix (TAS) based on collection of physiological, postural and visibility data during interaction analysis, and calculation of a consolidated User eXperience Index (UXI). Physiological data are based on heart rate parameters and eye pupil dilation parameters; postural data consists of analysis of main anthropometrical parameters; and interaction data from the system CAN-bus. Such a method can be adopted to assess interaction on field, during real task execution, or within simulated environments. It has been applied to a simulated case study focusing on agricultural machinery control systems, involving users with a different level of expertise. Results showed that TAS is able to validly objectify UX and can be used for industrial cases.

Keywords: Ergonomics | Human Factors | Human-centered design | User eXperience (UX) | Workload

Abstract: Transdisciplinarity is characterising numerous research areas, in which natural sciences are integrated with technical and social sciences, requiring mixed methodologies for achieving full sustainability. However, there is a lack of engineering methods and design tools able to effectively integrate the analysis of human performance and social impacts with technical issues during product and process design. In this context, digital manufacturing tools and virtual simulation technologies can be validly used to create interactive digital mock-ups where human-system interaction during manufacturing operations can be simulated to support product and process design. The paper proposes a mixed reality (MR) set-up to support human-centred product and process design, where systems and humans interacting with them are monitored and digitalised to easily evaluate the human-machine interaction, with the scope to have feedback for design optimisation. Such an approach is defined as trans disciplinary since it merges technical design issues and human perspectives to design products on the basis of effective human performance, with the goal to early detect design criticalities and improve the overall system design. Industrial use cases have been developed to demonstrate the validity of the proposed approach to support human-centred design of a tractor. Results have demonstrated potential improvements, in terms of time saving for design review and workers’ training, reduction of physical prototypes for design validation, reduction of late design and engineering changes, reduction of ergonomic issues, and global positive impact on time-to-market.

Keywords: human factors | human-centered design | transdisciplinary engineering | Virtual manufacturing | virtual reality (VR)

Abstract: Nowadays, robots are heavily used in factories for different tasks, most of them including grasping and manipulation of generic objects in unstructured scenarios. In order to better mimic a human operator involved in a grasping action, where he/she needs to identify the object and detect an optimal grasp by means of visual information, a widely adopted sensing solution is Artificial Vision. Nonetheless, state-of-art applications need long training and fine-tuning for manually build the object's model that is used at run-time during the normal operations, which reduce the overall operational throughput of the robotic system. To overcome such limits, the paper presents a framework based on Deep Convolutional Neural Networks (DCNN) to predict both single and multiple grasp poses for multiple objects all at once, using a single RGB image as input. Thanks to a novel loss function, our framework is trained in an end-to-end fashion and matches state-of-art accuracy with a substantially smaller architecture, which gives unprecedented real-time performances during experimental tests, and makes the application reliable for working on real robots. The system has been implemented using the ROS framework and tested on a Baxter collaborative robot.

Keywords: Collaborative robotics | Deep learning | Industry 4.0 | Vision-guided robotic grasping

Abstract: Deburring operations are critical to automate when high quality is required, due to the unpredictable presence and variable thickness of burrs that necessitate singular optimized process planning. Industrial anthropomorphic manipulators could effectively perform high quality deburring operations, but still lack the intelligence needed to generate quality and time-optimal deburring cycles. This paper presents a novel architecture of Zero Defect intelligent deburring robotic cells. Vision systems and metrological sensors allow the identification of the burrs and the overall quality and pose of the workpiece, while a novel model-based supervisory control, based on a digital twin, automatically calculates the optimal sequence of operations and working parameters needed to achieve the desired quality, generating also the PLC and robot controllers validated code to perform each task. Finally, the prototype of the proposed Zero Defect intelligent deburring cell has been developed.

Keywords: Digital twin | Engineering methods | Industry 4.0 | Robotic manufacturing | Virtual prototyping | Zero defect manufacturing

Abstract: Industry 4.0 leverages Cyber Physical Production Systems (CPPS) that use IoT (Internet of Things) communication and ubiquitous computing to optimize and integrate synergistically manufacturing processes and industrial business. This increased computational and communication capability allows to dynamically interact with the physical environment providing higher performance leading the fourth industrial revolution. The benefits generated by the involvement of the TOGAF Framework in the most varied organizational models were previously discussed in the literature in a broad way, different from the application of IoT architecture, recently studied and applied in the industrial branch. Therefore, no IoT application activities based on the TOGAF structure in manufacturing processes were identified. To explore this interactivity in IoT based manufacturing systems, this paper seeks to investigate how industrial IoT application architectures are built and correlate them with the framework TOGAF (The Open Group Architecture Framework). The development of the article is defined in three steps: (i) to review the literature within the industrial context in order to consolidate the information and address different representations of the study in question to confirm the gap presented earlier; (ii) to verify the various ways to structure the information for IoT applications and correlate them with the TOGAF framework; and (iii) to elaborate a consistent critical analysis from the addressed points.

Keywords: Architecture | Internet of things | IoT | TOGAF

Abstract: Additive Manufacturing (AM) technologies have greatly extended design possibilities and freedom. However, in the designer everyday work, the decision regarding the adoption of AM for some components is not straightforward. There is a need to evaluate the properties of the available materials, their compatibility with the specific application, redesign shapes accordingly to additive rather than subtractive or deforming processes, conceive merging components in unique complex multifunctional parts. Indeed, economic, procurement and logistics evaluations, possibly extended to the entire life cycle, are necessary to come to a decision for a new and radical solution. In this context, the paper investigates the complex set of information involved in the process to guide a designer in a structured assessment and evaluation of opportunities for the adoption of AM. The approach includes the analysis of the design requirements to evaluate the applicability of additive technologies. Selected design questions are presented as attention points to help designers in the decision-making process along with a metric to merge the answers in an overall compliance index. Finally, some test cases from the literature and industry are reported to validate the proposed decision process.

Keywords: Additive manufacturing | Decision-making | Design for additive manufacturing | Design process

Abstract: Human-centered design is based on the satisfaction of the user needs mainly related to performances, interaction, usability, accessibility, and visibility issues. However, the quality of the interaction process is hidden and usually difficult to detect. The paper proposes a multi-disciplinary assessment tool for the evaluation of the human-machine interaction, based on the collection of physiological data and anthropometrical performance data. Such a method can be used both within on-field tests and virtual simulations, supporting the spread of digital approaches in industry. The methodology allows objectifying how users interact with machine or interface items, thanks to the collection of the users’ performance during task execution, the digitalization of collected data, and the evaluation of users’ physical and mental workload. Such a system has been applied to an industrial case study focusing on agricultural machinery driving and control to support the system re-design in terms of interface features, commands’ location and grouping, and positioning of additional devices.

Keywords: Digital factory | Ergonomics | Human factors | Human-centered design | Human-machine interaction

Abstract: In the context of smart factories, where intelligent machines share data and support enhanced functionalities at a factory level, workers are still seen as spectators rather than active players (Hermann, Pentek, & Otto, 2017). Instead, Industry 4.0 represents a great opportunity for workers to become part of the intelligent system; on one hand, operators can generate data to program machines and optimize the process flows, on the other hand they can receive useful information to support their work and cooperate with smart systems (Romero et al., 2016). Diversely from machines, humans are naturally smart, flexible and intelligent, so putting the operators in the digital loop can bring more powerful and efficient factories. The paper aims at defining a theoretical human-centered framework for Operator 4.0, and testing its feasibility and impact on companies, thanks to the integration of human factors in 4.0 computerized industrial contexts. The proposed framework is based on data collection about the workers’ performance, actions and reactions, with the final objective to improve the overall factory performance and organization. Data are used to assess the workers’ ergonomics performance and perceived comfort and to build a proper knowledge about the human asset of the factory, to be integrated with the knowledge derived from machine data collection. The framework is cased on the adoption of an Operator 4.0 monitoring system, which consists of an eye tracking and a wearable biosensor, combined to a proper protocol analysis to interpret data and create a solid knowledge. Virtual prototypes are used to make the workers interact with the digital factory to conveniently simulate the human–machine interaction (HMI) in order to avoid bottlenecks at the shop floor, to optimize the workflows, and to improve the workstations’ design and layout. The study represents a step toward the design of human-centred industrial systems, including human factors in the digital twin. The research approach has been successfully tested on an industrial case study, developed in collaboration with CNH Industrial, for the re-design of assembly workstations.

Keywords: Digitization | Human factors | Industry 4.0 | Mixed reality | Operator 4.0

Abstract: At present, energy consumption strongly affects the financial payback period of industrial robots, as well as the related manufacturing process sustainability. Henceforth, during both design and manufacturing management stages, it becomes crucial to assess and optimize the overall energy efficiency of a robotic cell by means of digital manufacturing tools. In practice, robotic plant designers and managers should be able to provide accurate decisions also aimed at the energy optimization of the robotic processes. The strong scientific and industrial relevance of the topic has led to the development of many solutions but, unfortunately, state of the art industrial manipulators are equipped with closed controllers, which heavily limit the feasibility and performance of most of the proposed approaches. In light of the aforementioned considerations, the present paper presents a novel simulation tool, seamlessly interfaced with current robot offline programming tools used in industrial practices, which allows to automatically compute energy-optimal motion parameters, thus reducing the robot energy consumption, while also keeping the same productivity and manufacturing quality. The main advantage of this method, as compared to other optimization routines that are not conceived for direct integration with commercial industrial manipulators, is that the computed parameters are the same ones settable in the robot control codes, so that the results can automatically generate ready-to-use energy-optimal robot code. Experimental tests, performed on a KUKA Quantec KR210 R2700 prime industrial robot, have confirmed the effectiveness of the method and engineering tool.

Keywords: Automatic code generation | Energy optimization | Industrial robotics | Industry 4.0 | Robot offline programming | Sustainable manufacturing | Virtual prototyping

Abstract: Manufacturing ergonomics refers to the application of ergonomic principles and human factors analysis to the design of manufacturing tasks with the final aim to optimize the workers’ wellbeing and guarantee the expected process performance. Traditional design approaches are based on the observation of individual workers performing their jobs, the detection of unnatural postures (e.g., bending, twisting, overextending, rotating), and the definition of late corrective actions according to ergonomic guidelines. Recently, computer-integrated simulations based on virtual prototypes and digital human models (DHMs) can be used to assess manufacturing ergonomics on virtual manikins operating in digital workplaces. Such simulations allow validating different design alternatives and optimizing the workstation design before the creation, and pave the way to a new approach to manufacturing system design. The present paper aims at comparing different computer-integrated set-ups to support the design of human-centred manufacturing workstations. It defines a protocol analysis to support workstation design by analysing both physical and cognitive aspects, and applies the protocol within different digital set-ups. In particular, the study investigates a 2D desktop set-up using standardized DHMs and a 3D immersive mixed reality set-up based on motion capture of real workers’ acting into a mixed environment, comparing them with the traditional approach. An industrial case study focusing on design optimization of a manufacturing workstation in the energy industry is used to test the effectiveness of the two digital set-ups for the definition of re-design actions.

Keywords: Digital human models | Human factors | Human-centred design | Manufacturing ergonomics | Mixed reality

Abstract: Today manufacturing enterprises aim not only to deliver high-value, cost-effectively products in a sustainable way, but also to consider the quality of the working environments. The analysis of human factors, which strongly affect time and quality of manufacturing processes, are crucial for satisfying people involved in the manufacturing process and making them safe, preventing diseases, errors and excessive workload. The paper presents a structured procedure to automatically extract data from virtual analysis made by digital manufacturing tools and measure a set of indicators to validly assess manufacturing ergonomics. The research considers the state of the art in manufacturing ergonomics and defines a set of indicators suitable for manufacturing manual operations, focusing on assembly tasks. Furthermore, it defines a methodology to automatically extract data valorising the selected indicators and an application, based on Visual Basic, to generate the specific task list and related assessment. The result is a rapid and objective assessment, independent from the experience of the user, which can be executed during process design. The procedure has been applied to an industrial case study, where the manual assembly of cabin supports on the tractor chassis has been analysed in order to correct the most uncomfortable steps and obtain a more ergonomic process. A decrease of the EAWS score, calculated with the proposed method, allowed to validate the proposed solution, suggesting a redesign of the assembly cycle to improve the working conditions. Such a procedure anticipates the analysis of the workers' wellbeing during the design stage to support the definition of human-centric manufacturing processes, simplifying and accelerating the assessment activities.

Keywords: Digital Manufacturing | Human Factors | Human-Centered Design (HCD) | Manufacturing Ergonomics | Virtual Engineering

Abstract: Although the so-called Industry 4.0 trend is promoting the increasing automation of processes in the factories of the future, manual activities still play an extremely important role within the factory and human factors greatly affect the process performance. However, the analysis of human-machine interaction and the prediction of human performance in industry are difficult but crucial to have an optimized design of workspaces and interfaces, reducing time and cost of implementation, and avoiding late design changes. This research adopts a multimodal human-centered approach for the analysis of human-machine interaction, and proposes a multimodal experimental set-up for the evaluation of the workers' experience to support the design of industrial workstations. The set-up combines virtual mockups, interaction with both physical and virtual objects, and monitoring sensors to track users and analyze their actions and reactions. It allows creating a multimodal environment able to deepen the interaction between humans and systems or interfaces, to support design activities. Indeed, it has been demonstrated that the analysis of the reactions of the users involved, allows to evaluate the quality of the interaction, identify the critical issues, define corrective actions, and propose guidelines for system design or redesign [1]. The paper describes the application of the proposed set-up on two industrial case studies and reports the main results.

Keywords: Digital Manufacturing | Human Factors | Human-Centered Design | Industry 4.0 | Virtual Reality

Abstract: Robotic deburring (RD) still requires long and delicate physical tests to tune the process-parameters, thus drastically reducing the robotic cell productivity. Henceforth, engineering methods and tools are needed to optimise the RD application within a virtual environment, replicating the real behaviour of the robot tooling under different process conditions, namely unpredictable variety of burr size/shape and limited accuracy of the robot motions. To this purpose, the spindle compliance, which plays a fundamental role, is unfortunately not evaluated by state-of-the-art simulation tools. The present paper proposes a virtual prototype (VP) of a radially-compliant spindle, suitable to assess and optimise the deburring efficiency in different case scenarios. A multi-body model of the spindle, integrated with the process behavioural model, predicts process forces and optimal deburring parameters, delivering the contour maps of the envisaged deburring error as function of feed rate and tool compliance. An industrial case-study is provided.

Keywords: parameter design | passively compliant spindle | robotic deburring | virtual prototyping

Abstract: Human-centred design is based on the satisfaction of the user needs mainly related to performances, interaction, comfort, usability, accessibility, and visibility issues. However, the “real” user experience (UX) is hidden and usually difficult to detect. The paper proposes a multimodal system based on the collection of physiological and anthropometrical performance data on field and within a mixed prototyping set-up. The mixed environment makes users interact with virtual and digital items and users’ performance to be capture and digitalized, simulating human-machine interaction, while physiological and anthropometrical data collection allows to objectify the users’ physical and mental workload during task execution. Such a system has been applied to an industrial case study focusing on agricultural machinery driving and control to support the definition of a new cabin and its control board, in terms of seat features, commands’ positioning and grouping, and positioning of additional devices.

Keywords: Ergonomics | Human-centred design | Human-machine interaction | Mixed prototyping | User experience

Abstract: The analysis of workers’ ergonomics and human factors is assuming a great importance in product and process design for modern industry. However, there is a lack of common references and structured protocols for the assessment of workers’ experience in industrial practices in an effective and predictive way. As a result, designers are poorly supported in the application of digital technologies, which are demonstrating to have a great potential. This ascertainment suggested defining a reference model to analyse the so-called user experience (UX) of workers and a proper technological set-up based on virtual simulations in order to support human-centred product-process design. Indeed, the recent advances in ubiquitous computing, wearable technologies and low-cost connected devices offer a huge amount of new tools for human data monitoring. However, the open issue is selecting the most proper devices for industrial application area in respect with design goals, using virtual simulation and digital manufacturing tools. The research proposed a structured procedure to use existing digital technologies to support product-process design to analyse the workers behaviours and assess the perceived experience for industrial scopes. The paper defined a structured protocol analysis to objectify and measure the workers’ experience with the final aim to support the requirements definition in product-process design by using digital technologies. In particular, the model has been defined for the automotive sector. The paper contribution is the definition of the protocol analysis and the development of a mixed reality (MR) set-up to involve real users’ and to improve the digital models. Such a protocol has been applied to different industrial cases related to product and process design, developed in collaboration with CNH Industrial. The comparison with traditional design procedures highlighted the benefits of adopting virtual mock-up and digital simulation within a MR environment to shorten design time and improve the design overall quality.

Abstract: Human factors are fundamental for manufacturing sustainability, which is determined by social, economic and environmental performance. However, there is a lack of engineering methods and tools that are able to integrate their analysis with product and process optimisation according to sustainability principles. The present study proposes an analytical approach to support sustainable manufacturing (SM) by analysing the so-called user experience (UX) of manufacturing and assembly processes starting from the early design stages. Considering both behavioural and cognitive aspects of manufacturing UX and defining a corresponding model, it is possible to estimate the UX impact on manufacturing sustainability for a certain product and its related processes. The proposed method is implemented in a computer-based framework, which can be easily integrated with environmental and cost assessment tools to integrate all three SM aspects. Finally, a case study focused on automated machines is presented; the proposed approach was used to redesign the machine to improve its economic, environmental and human-related impacts. The industrial case study provides concrete evidence of the achievable benefits of applying the proposed model in manufacturing practice. Indeed, the case study demonstrated how the manufacturing and assembly process of a specific machine was optimised by simplifying the product structure, changing the adopted materials and creating more human-centred activities. The new solution is more sustainable due to time savings (−30%), cost reduction (−20%), reduced environmental impact (−25%) and improved UX (+30%).

Keywords: computer-integrated approach | design for manufacturing & assembly (DFMA) | human factors | sustainability | user experience

Abstract: Nowadays industrial products require numerous aspects to be integrated and optimized contemporarily and interactively: mechanics, electronics, system control, management of material and information flows, interfaces, human-product interaction, as well as impacts on environment, costs and human factors. As a consequence, the design of industrial products has to combine new advanced functionalities and high performances by limiting production cost as well as environmental and social impacts. It means that the entire industrial system has to be designed looking towards sustainability. While attention to cost and environmental performance is not new, the analysis of social-related aspects is basically unexplored for industrial products. Achieving social sustainability includes forecasting human behaviours, actions and reactions, analysing how human beings interact with objects, tools, devices and interfaces, and assessing their physical and mental workload. The present research proposes an analytical approach to support the design of industrial products by providing an early sustainability assessment of the three aspects of sustainability (environment, cost and people). It adopts a feature-based approach and a set of key performance indicators (KPIs) to assess the sustainability of the manufacturing and assembly processes and to support an easy and preventive analysis during product design. The paper presents the application of such method to industrial cases.

Keywords: Design for Sustainability | Feature-based Analysis | Key Performance Indicators | Sustainability Assessment | Sustainable Manufacturing

Abstract: Design for serviceability begins with understanding the customer needs related to availability, reliability, accessibility and visibility, and aims at designing optimized systems where maintenance operations are easy and intuitive in order to reduce the time to repair and service costs. However, service actions are difficult to predict in front of a traditional CAD model. In this context, digital manufacturing tools and virtual simulation technologies can be validly used to create mixed digital environments where service tasks can be simulated in advance to support product design and improve maintenance actions. Furthermore, the use of human monitoring sensors can be used to detect the stressful conditions and to optimize the human tasks. The paper proposes a mixed reality (MR) set-up where operators are digitalized and monitored to analyse both physical and cognitive ergonomics. It is useful to predict design criticalities and improve the global system design. An industrial case study has been developed in collaboration with CNH Industrial to demonstrate how the proposed set-up is used for design for serviceability, on the basis of experimental evidence.

Keywords: Design for serviceability | Digital Manufacturing (DM) | Ergonomics | Human-Centred Design (HCD) | Sustainability | Virtual Simulation

Abstract: Collaborative robots must operate safely and efficiently in ever-changing unstructured environments, grasping and manipulating many different objects. Artificial vision has proved to be collaborative robots’ ideal sensing technology and it is widely used for identifying the objects to manipulate and for detecting their optimal grasping. One of the main drawbacks of state of the art robotic vision systems is the long training needed for teaching the identification and optimal grasps of each object, which leads to a strong reduction of the robot productivity and overall operating flexibility. To overcome such limit, we propose an engineering method, based on deep learning techniques, for the detection of the robotic grasps of unknown objects in an unstructured environment, which should enable collaborative robots to autonomously generate grasping strategies without the need of training and programming. A novel loss function for the training of the grasp prediction network has been developed and proved to work well also with low resolution 2-D images, then allowing the use of a single, smaller and low cost camera, that can be better integrated in robotic end-effectors. Despite the availability of less information (resolution and depth) a 75% of accuracy has been achieved on the Cornell data set and it is shown that our implementation of the loss function does not suffer of the common problems reported in literature. The system has been implemented using the ROS framework and tested on a Baxter collaborative robot.

Keywords: Collaborative robotics | Deep learning | Engineering methods | Vision-guided robotic grasping

Abstract: Human-centred design is based on the satisfaction of the user needs related to performances, aesthetics, reliability, usability, accessibility and visibility issues, costs, and many other aspects. The combination of all these aspects has been called as “perceived quality”, that is definitely a transdisciplinary topic. However, the “real” perceived quality is usually faithfully assessed only at the end of the design process, while it is very difficult to predict on 3D CAD model. In this context, digital manufacturing tools and virtual simulation technologies can be validly used according to a transdisciplinary approach to create interactive digital mock-ups where the human-system interaction can be simulated and the perceived quality assessed in advance. The paper proposes a mixed reality (MR) set-up where systems and humans interacting with them are digitalized and monitored to easily evaluate the human-machine interaction. It is useful to predict the design criticalities and to improve the global system design. An industrial case study has been developed in collaboration with CNH Industrial to demonstrate how the proposed set-up can be validly used to support human-centred design.

Keywords: Digital manufacturing | Human-centred design | Human-machine interaction | Virtual simulation

Abstract: Industrial process plants are increasingly becoming complex structures with high level of automation. Nonetheless, the final plant productivity and the overall equipment efficiency does not solely depend on an optimized engineering design/installation practice, but also on human operators supervision. In parallel, along with the classic demand to minimize costs and time-to-market during the design phases, issues concerning human safety and failure prevention play a crucial role, one of the highest target being the avoidance of dangerous process states. Within this context, Simulation-Based-Training (SBT) allows plant operators to learn how to command complex automated machineries within a secure virtual environment. Similar to its usage in medical, aerospace, naval and military fields, SBT for manufacturing systems can be employed in order to involve the user within a realistic scenario, thus providing an effective, lifelike, interactive training experience under the supervision of experienced personnel. In addition, also according to previous literature, industry-driven SBT may be effectively envisaged as a natural extension of the plant life-cycle simulation practice, comprising Design Simulation & Optimization, Virtual Commissioning, Operator Training, up to Plant Maintenance. In this context, since the overall system behavior depends both on manufacturing process dynamics and Control Logics, the main challenge for an effective SBT is related with the development of a real-time environment where control system responsiveness is fully reproduced. Owing to this consideration, this paper reports a successful industrial case study, concerning a novel SBT workbench used for steel plants operator training, discussing both the virtual prototyping phase and the development of a real-time simulation architecture. In particular, a hybrid process simulation is employed, where a virtual process model is coupled with physical PLC and Human–Machine Interface, thus achieving an accurate reproduction of the real plant/operator interaction.

Keywords: Hybrid virtual/physical simulation | Industrial case study | Simulation-based-training | Virtual commissioning | Virtual prototyping

Abstract: This paper presents a new method for optimizing the layout position of several Industrial Robots (IRs) placed within manufacturing work-cells, in order to execute a set of specified tasks with the minimum energy consumption. At first, a mechatronic model of an anthropomorphous IR is developed, by leveraging on the Modelica/Dymola built-in capabilities. The IR sub-system components (namely mechanical structure, actuators, power electronic and control logics) are modeled with the level of detail strictly necessary for an accurate prediction of the system power consumption, while assuring efficient computational efforts. Secondly, once each IR task is assigned, the optimal work-cell layout is computed by using proper optimization techniques, which numerically retrieve the IR base position corresponding to the minimum energy consumption. As an output to this second development stage, a set of color/contour maps is provided, that depicts both energy demand and time required for the task completion as function of the robot position in the cell to support the designer in the development of an energy-efficient layout. At last, two robotic manufacturing work-cells are set-up within the Delmia Robotics environment, in order to provide a benchmark case study for the evaluation of any energy saving potential. Numerical results confirm possible savings up to 20% with respect to state-of-the-art work-cell design practice.

Abstract: The so-called smart manufacturing systems (SMS) combine smart manufacturing technologies, cyber-physical infrastructures, and data control to realize predictive and adaptive behaviours. In this context, industrial research focused mainly on improving the manufacturing system performance, almost neglecting human factors (HF) and their relation to the production systems. However, in order to create an effective smart factory context, human performance should be included to drive smart system adaptation in efficient and effective way, also by exploiting the linkages between tangible and intangible entities offered by Industry 4.0. Furthermore, modern companies are facing another interesting trend: aging workers. The age of workers is generally growing up and, consequently, the percentage of working 45–64 years old population with different needs, capabilities, and reactions, is increasing. This research focuses on the design of human-centred adaptive manufacturing systems (AMS) for the modern companies, where aging workers are more and more common. In particular, it defines a methodology to design AMS able to adapt to the aging workers’ needs considering their reduced workability, due to both physical and cognitive functional decrease, with the final aim to improve the human-machine interaction and the workers’ wellbeing. The paper finally presents an industrial case study focusing on the woodworking sector, where an existing machine has been re-designed to define a new human-centred AMS. The new machine has been engineered and prototyped by adopting cyber-physical systems (CPS) and pervasive technologies to smartly adapt the machine behaviour to the working conditions and the specific workers’ skills, tasks, and cognitive-physical abilities, with the final aim to support aging workers. The achieved benefits were expressed in terms of system usability, focusing on human-interaction quality.

Keywords: Adaptive manufacturing systems | Aging workers | Cyber-physical systems | Human factors | Smart manufacturing systems | Usability

Abstract: Virtual prototyping enables the validation and optimization of mechanical devices similar to physical testing, saving time and costs in the product development, especially in case of heavy machines with complex motions. However, virtual prototyping is usually deployed only at the end of the design process, when the product architecture has already been developed. The present paper discusses the introduction of virtual prototypes since the conceptual design stage as “Virtual Concepts”, in which coarse models of machinery design variants are simulated to interactively evaluate several solutions and support best design choices. Virtual concept modeling and interactive preliminary validation, along with its later integration into a virtual prototype, are expressly investigated using multi body dynamics software. A verification case study concerning a large vibrating screen is presented, in order to demonstrate that dynamic virtual concepts can enable an easier and effective interactive evaluation of the design variants, thus increasing the design process predictability. Finally, current challenges to be solved for the practical adoption of virtual concept simulations as an integral part of the industrial design process are critically discussed.

Keywords: CAD based simulation | Design process | Vibrating screen | Virtual concepts | Virtual prototyping

Abstract: Although factories are becoming smarter and more and more automated, thanks to ICT penetration, process performances still highly depend on 'humans in the loop' who have to carry out their tasks by perceiving and understanding increasingly complex multidimensional data sets. Forecasting the human behaviours and assessing how human factors affect the process performance are very difficult but fundamental for strategic decision-making and sustainable manufacturing. In this context, the research highlights the need of predictive methods to design human-centred smart manufacturing systems from the early design stages as an important part of the overall assessment of process sustainability. The paper defines a model to early assess human factors to be integrated with other existing models (i.e., cost estimation and lifecycle assessment) to evaluate manufacturing process sustainability. The proposed integrated method can be fruitfully used to support the design of sustainable manufacturing systems by taking into account also the impact on workers. An industrial case study focusing on packaging machines design is presented to demonstrate the validity of the proposed method and its adoption to propose re-design action promoting sustainability.

Keywords: Design for sustainability | Human factors | Key performance indicators | KPIs | Sm | Sustainability assessment | Sustainable manufacturing

Abstract: Nevertheless process automation is a global trend, some specific phases (i.e., assembly) in highly technological sectors (i.e., medical, pharmaceutical, diagnostics, dental) are still managed by human workers, due to high-precision tasks and low production volumes. In this context, operators are forced to work faster and adapt to not ergonomically workstations and workflows. As a consequence, human assembly is frequently the bottleneck of the entire process due a not ergonomic layout and process design. The study was conducted at a medical equipment manufacturer, leader of dental equipment production, and focused on the analysis of the assembly process of the dental units. Workers at the assembly line were observed by experts and involved also by interviews and focus groups to detect the assembly issues and process jam. The research provides a valuable example of how physical, cognitive and organizational ergonomic problems affect the final process performance and how human-oriented re-design actions can be easily defined according to the proposed analysis procedure.

Keywords: Assembly workstation design | Design optimization | Ergonomics | Human Factors | Humancentred design

Abstract: Anticipating the analysis of cost and performances before the detailed design stage is difficult, but possible thanks to a synthetic analysis of the manufacturing knowledge, a successful collaboration among the numerous actors involved, and a methodology able to highlight the cost issues and to guide a costoriented machine design. This paper presents a methodology integrating Design for Manufacturing and Assembly (DFMA), Design To Cost (DTC), and Value Analysis (VA) to support companies in cost-effective machine design and costoriented re-engineering. This paper demonstrates the validity of the proposed methodology by an industrial case study focusing on packaging machines, developed in collaboration with a world leader company in tissue packaging machines. Thanks to the proposed approach, the company was able to identify those parts to be re-engineered (e.g., oversized parts, parts with unnecessary tolerances, similar parts to be merged into a unique one, common groups to be reused in similar machines, parts or material substitutions, wrong suppliers' selection) and possible technological improvements. A significant cost optimization and global machine sustainability improvement were achieved on a specific packaging machine line, mainly due to product structure simplification, part reuse, improved design solutions, and optimization of selected manufacturing processes.

Keywords: Cost optimization | Design for Manufacturing and Assembly | Design To Cost | Sustainability | Value analysis

Abstract: The analysis of human factors is assuming an increasing importance in product and process design and the lack of common references for their assessment in industrial practices had driven to define a reference model to analyse the so-called User eXperience (UX) to support human-centred product-process design. Indeed, the recent advances in ubiquitous computing, wearable technologies and low-cost connected devices offer a huge amount of new tools for UX monitoring, but the main open issue is selecting the most proper devices for the specific application area and properly interpreting the collected information content in respect with the industrial design goals. The research investigates how to analyse the human behaviours of "users" (i.e., workers) by a reference model to assess the perceived experience and a set of proper technologies for UX investigation for industrial scopes. In particular, the model has been defined for the automotive sector. The paper defines a set of evaluation metrics and a structured protocol analysis to objectify and measure the UX with the final aim to support the requirements definition in product-process design. The model has been defined to fit different cases: vehicle drivers at work, workers in the manufacturing line, and service operators.

Keywords: Digital mock-ups | Human Factors | Integrated product-process design | Protocol analysis | User eXperience

Abstract: This paper presents a novel robot simulation tool, fully interfaced with a common Robot Offline Programming software (i.e. Delmia Robotics), which allows to automatically compute energy-optimal motion parameters, for a given end-effector path, by tuning the joint speed/acceleration during point-to-point motions whenever allowed by the manufacturing constraints. The main advantage of this method, as compared to other optimization routines that are not conceived for a seamless integration with commercial industrial manipulators, is that the computed parameters are the same required by the robot controls, so that the results can generate ready-to-use energy-optimal robot code.

Keywords: Computer-Aided Robotic tools | Delmia Robotics | Energy Optimization | Industrial Robots | Sustainable Manufacturing

Abstract: The energy consumption and electrical characteristics of a novel direct current (DC) power supplied industrial robot prototype are compared and analyzed with a state of the art alternating current (AC) supplied industrial robot. An extensive set of experiments shows an important reduction of the total energy consumption for different electrical power profiles measured in various robot trajectories with specific working temperatures. The recuperated energy is also analyzed in the different scenarios. Experimental results show that a DC type robot can be up to 12.5% more energy-efficient than an equivalent AC type robot.

Keywords: AC/DC micro-grids | energy consumption | energy efficient robotics | energy measurements | sustainable manufacturing

Abstract: Sustainable Manufacturing (SM) traditionally focused on optimization of environmental and economic aspects, by neglecting the human performance. However, the industrial plant's costs, productivity and process quality highly depend on the individual human performance (e.g., comfort perceived, physical and mental workload, simplicity of actions, personal satisfaction) and how much hazardous positions and uncomfortable tasks finally cost to the company. The present paper defines a human-centred virtual simulation environment to optimize physical ergonomics in workstation design and demonstrates its benefits on an industrial case study in pipe industry. The proposed environment aims at overcoming traditional approaches, where analysis are carried out at the shop-floor when the plant is already created, by providing a virtual environment to easily test and verify different design solutions to optimize physical, cognitive and organizational ergonomics.

Keywords: Digital Human Models (DHM) | Human-Centred Design (HCD) | Manufacturing Ergonomics | Virtual Reality | Workstation design

Abstract: The paper presents a distributed model for implementing Cyber-Physical Systems aimed at controlling physical entities through the Internet of Things. The model tames the inherent complexity of the task by a recursive notion of modularity which makes each module both a controller and a controlled entity. Modules are arranged along part-whole tree-like hierarchies which collectively constitute the system. The behaviour of each module is strictly local since it has visibility only on its controlled modules, but not on the module which controls it. Each behaviour can be thus checked locally at design time against safety and liveness formulas, which still hold when component holons are composed into more complex ones, thus contributing, without the need of additional checks, to the overall safety and liveness of the final system.

Keywords: Cyber-Physical Systems | Holons | Industry 4.0 | Internet of Things | Safety engineering | Smart factories | State-based Control

Abstract: Industry 4.0 paradigm is based on systems communication and cooperation with each other and with humans in real time to improve process performances in terms of productivity, security, energy efficiency, and cost. Although industrial processes are more and more automated, human performance is still the main responsible for product quality and factory productivity. In this context, understanding how workers interact with production systems and how they experience the factory environment is fundamental to properly model the human interaction and optimize the processes. This research investigates the available technologies to monitor the user experience (UX) and defines a set of tools to be applied in the Industry 4.0 scenario to assure the workers’ wellbeing, safety and satisfaction and improve the overall factory performance.

Keywords: Human Factors | Human Interaction | Industry 4.0 | Production system design | User experience

Abstract: In order to achieve more sustainable development processes, industries need not only to improve energy efficiency and reduce costs, but also to increase the operators’ wellbeing to promote social sustainability. In this context, the present research focuses on the definition of a methodology based on human-centred virtual simulation to improve the social sustainability of maintenance tasks by enhancing system design and improving its serviceability. It is based on the operators’ involvement and the analysis of their needs from the early design stages on virtual mock-ups. The methodology proposed merges a protocol analysis for human factors assessment and an immersive virtual simulation where immersive serviceability simulations can be used during design phases. To demonstrate the effectiveness of the proposed method, an industrial use case has been carried out in collaboration with CNH Industrial.

Keywords: Ergonomics | Human-Centred Design (HCD) | Serviceability | Sustainability | Virtual simulation

Abstract: According to recent researches, it is desirable to extend Industrial Robots (IR) applicability to strategic fields such as heavy and/or fine deburring of customized parts with complex geometry. In fact, from a conceptual point of view, anthropomorphic manipulators could effectively provide an excellent alternative to dedicated machine tools (lathes, milling machines, etc.), by being both flexible (due to their lay-out) and cost efficient (20-50% cost reduction as compared to traditional CNC machining). Nonetheless, in order to successfully enable highquality Robotic Deburring (RD), it is necessary to overcome the intrinsic robot limitations (e.g. reduced structural stiffness, backlash, time-consuming process planning/optimization) by means of suitable design strategies and additional engineering tools. Within this context, the purpose of this paper is to present recent advances in design methods and software platforms for RD effective exploitation. Focusing on offline methods for robot programming, two novel approaches are described. On one hand, practical design guidelines (devised via a DOE method) for optimal IR positioning within the robotic workcell are presented. Secondly, a virtual prototyping technique for simulating a class of passively compliant spindles is introduced, which allows for the offline tuning of the RD process parameters (e.g. feed rate and tool compliance). Both approaches are applied in the design of a robotic workcell for high-accuracy deburring of aerospace turbine blades.

Keywords: Engineering methods | Industrial robotics | Intelligent factory | Virtual prototyping

Abstract: Analysis of human-related aspects is fundamental to guarantee workers’ wellbeing, which directly limits errors and risks during task execution, increases productivity, and reduces cost [1]. In this context, virtual prototypes and Digital Human Models (DHMs) can be used to simulate and optimize human performances in advance, before the creation of the real machine, plant or facility. The research defines a human-centred methodology and advanced Virtual Reality (VR) technologies to support the design of ergonomic workstations. The methodology considers both physical and cognitive ergonomics and defines a proper set of metrics to assess human factors. The advanced virtual immersive environment creates highly realistic and interactive simulations where human performance can be anticipated and assessed from the early design stages. Experimentation is carried out on an industrial case study in pipe industry.

Keywords: Digital Human Model | Ergonomics | Human-Centred Design | Sustainable Manufacturing | Virtual Reality

Abstract: Position-controlled Servo-Systems (SeSs) may be envisaged as a key technology to keep the manufacturing industry at the leading edge. Unfortunately, based on the current state-of-the-art, these mechatronic devices are well performing but intrinsically energy intensive, thus compromising the overall system sustainability. Therefore, traditional design and optimization paradigms, previously focused on productivity and quality improvement, should be critically reviewed so as to introduce energy efficiency as an optimality criterion alongside with the global production rate. In particular, focusing on mono-actuator systems with one degree-of-freedom, among the several design factors that can influence the SeS overall performance, the end-effector motion law can be easily modified without either hardware substitution or further investments. In this context, the purpose of the present paper is twofold. On one side, an effective method for the quick set-up of an energy-predictive CAD-based virtual prototype is discussed. In parallel, an energy comparison of some commonly employed Point-To-Point motions and optimization cost functions is provided. For what concerns the trajectory interpolation scheme, a standard optimization problem based on the aforementioned virtual model is solved by means of either algebraic or trigonometric splines. For what concerns the optimality criterion, either the system energy consumption or the root-means square value of the actuator torque are taken into account. In general, torque-based approaches, which may be preferred since they do not require a full knowledge of the SeS electrical parameters, can be effectively employed only when friction effects are negligible as compared to purely inertial loads. In parallel, cubic algebraic splines outperform other types of trajectories, although losing continuity of the resulting jerk profile.

Keywords: CAD/MBD tools | Eco-Design methods | Servo-Systems | Trajectory comparison | Virtual prototyping

Abstract: Industrial robotics provides high flexibility and reconfigurability supported by a user-friendly programming, but still lacks in accuracy. An effective workcell calibration reduces errors in robot manufacturing and enables robot machining applications. A novel workcell calibration method is embedded in an integrated design framework for an in-depth exploitation of CAD-based simulations and offline programming. The method is composed of two steps: first calibration of the workpiece-independent equipment in the workcell layout and final automated online calibration of workpiece-dependent equipment. The method is finally applied to a changeable robotic workcell for finishing aluminium cast housings for aerospace gear transmissions characterised by complex shapes and by close dimensional and geometrical specifications. Experimental results prove the method effectiveness in enhancing accuracy in robot machining.

Keywords: Aerospace industry | Industrial robotics | Integrated design | Workcell calibration

Abstract: Machining using industrial robots is currently limited to applications with low geometrical accuracies and soft materials. This paper analyzes the sources of errors in robotic machining and characterizes them in amplitude and frequency. Experiments under different conditions represent a typical set of industrial applications and allow a qualified evaluation. Based on this analysis, a modular approach is proposed to overcome these obstacles, applied both during program generation (offline) and execution (online). Predictive offline compensation of machining errors is achieved by means of an innovative programming system, based on kinematic and dynamic robot models. Real-time adaptive machining error compensation is also provided by sensing the real robot positions with an innovative tracking system and corrective feedback to both the robot and an additional high-dynamic compensation mechanism on piezo-actuator basis.

Keywords: Error compensation | Optical tracking | Robot dynamics | Robot modelling | Robotic machining

Abstract: In this paper, an engineering method for the power flow assessment of a position-controlled servo-mechanism is outlined. The considered system is composed of a permanent magnet synchronous motor coupled to a standard power converter, and directly connected to a slider crank mechanism. After the accurate description of a consistent power flow model, a sequential identification technique is discussed, which allows to determine the dynamic parameters of linkage, electric motor and electronic driver by means of non-invasive experimental measures. The proposed model allows to accurately predict the major sources of power loss within the system.

Keywords: Design of Experiments | Power flow assessment | Servo-actuated mechanism | Virtual prototyping

Abstract: Design for Sustainability (D4S) and LifeCycle Assessment (LCA) methods usually focus on one single aspect of sustainability at a time (e.g., environmental issues, ergonomics or costs) and are usually applied when the industrial system is already created, so that only corrective actions can be taken. In this context, the present research highlights the need of predictive methods to design sustainable system, able to provide an early holistic assessment from the early conceptual stages, and defines a set of models of impact able to assess all aspects of sustainability (i.e., environmental, economic and social) by proper key performance indicators (KPIs) from the early design stages. An industrial case study is presented to show the application of the proposed models on industrial manufacturing systems and demonstrate their validity in estimating the global impact on sustainability, including also human factors.

Keywords: Design for Sustainability | Design Methods | Human Factors | Key Performance Indicators (KPIs) | Lifecycle analysis | Sustainable Manufacturing

Abstract: Over the years cost optimization has gained a strategic importance to realize competitive products. However, traditional approaches are no longer efficient in modern highly competitive industrial scenarios, where numerous factors have to be contemporarily considered and optimized. In order to be effective, design has to care about cost along all its phases. This paper presents a methodology that integrates Design-To-Cost (DTC), Design for Manufacturing and Assembly (DFMA), Human Factors (HF) and Feature-Based Costing (FBC) to include costs from the early conceptual design stages and properly drive the product design. Thanks to a structured knowledge base and a FBC approach, it predicts both manufacturing and assembly processes from the 3D geometrical models and estimate the global costs, more accurately than existing tools. The research demonstrates the method validity by an industrial case study focusing on cost optimization of packaging machines. Thanks to the proposed method, the main design inefficiencies are easily identified from the early design stages and optimization actions are taken in advanced, in respect to traditional design process. Such actions allowed reducing total industrial costs of 20%, improving machine assemblability and human ergonomics due to structure simplification, part number reduction, and production processes modification, and reducing the time spent for cost estimation (until -60%).

Keywords: Cost modeling | Cost optimization | Design-to-Cost (DTC) | Feature-Based Costing (FBC) | Knowledge-Based engineering (KBE)

Abstract: At the current state-of-the-art, Robotic Deburring (RD) has been successfully adopted in many industrial applications, but it still needs improvements in terms offinal quality. In fact, the effectiveness of a RD process is highly influenced by the limited accuracyof the robot motions and by the unpredictable variety of burr size/shape. Tool compliance partially solves the problem, although dedicated engineering design tools are strictly needed, in order to identify those optimized parameters and RD strategies that allow achieving the best quality and cost-effectiveness. In this context, the present paper proposes a CAD-based Virtual Prototype (VP) of a pneumatic compliant spindle, suitable to assess the process efficiency in different case scenarios. The proposed VP is created by integrating a 3D multi-body model of the spindle mechanical structure with the behavioural model of the process forces, as adapted from previous literature. Numerical simulations are provided, concerning the prediction of both cutting forces and surface finishing accuracy.

Keywords: CAD-based tools | Compliant spindle | Robotic deburring | Virtual Prototyping

Abstract: Industrial Robotics (IR) may be envisaged as the key technology to keep the manufacturing industry at the leading edge. Unfortunately, at the current state-of-the-art, IR is intrinsically energy intensive, thus compromising factories sustainability in terms of ecological footprint and economic costs. Within this scenario, this paper presents a new framework called AREUS, focusing on eco-design, eco-programming and Life Cycle Assessment (LCA) of robotized factories. The objective is to overcome current IR energetic limitations by providing a set of integrated technologies and engineering platforms. In particular, novel energy-saving hardware is firstly introduced, which aim at exchanging/storing/recovering energy at factory level. In parallel, innovative engineering methods and software tools for energy-focused simulation are developed, as well as energy-optimal scheduling of multi-robot stations. At last, LCA methods are briefly described, which are capable to assess both environmental and economic costs, linked to the flows of Material, Energy and Waste (MEW). A selected list of industrially-driven demonstration case studies is finally presented, along with future directions of improvement.

Keywords: Computer-Aided-Robotics | DC-grid | Energy-Efficient Industrial Robotics | LCA | Optimal Sequences

Abstract: This paper quantitatively reports about a practical method to improve both position accuracy and energy efficiency of Servo-Actuated Mechanisms (SAMs) for automated machinery. The method, which is readily applicable on existing systems, is based on the 'smart programming' of the actuator trajectory, which is optimized in order to lower the electric energy consumption, whenever possible, and to improve position accuracy along those portions of the motion law which are process relevant. Both energy demand and tracking precision are computed by means of a virtual prototype of the system. The optimization problem is tackled via a traditional Sequential-Quadratic-Programming algorithm, that varies the position of a series of virtual points subsequently interpolated by means of cubic splines. The optimal trajectory is then implemented on a physical prototype for validation purposes. Experimental data confirm the practical viability of the proposed methodology.

Keywords: Energy Efficiency | Position Accuracy | Trajectory Optimization | Virtual Prototyping

Abstract: Programmable servo-actuated mechanisms can enhance the flexibility and the reconfigurability of modern manufacturing systems. Differently from fully mechanical design solutions (such as mechanical cams) and especially in the case of high-dynamic motions, servomechanism performance depends on several interacting factors, namely electric motor and linkage dynamics, controller efficacy, and requested motion law. In particular, point-to-point (PTP) trajectories are usually designed in order to comply with technological constraints, imposed by the required interaction with the handled product, and to maximize some optimality criterion such as, for instance, energy efficiency or limited actuation torques. In this context, the present paper proposes a novel method for designing energy and peak-power optimal PTP motions. A standard optimization problem is solved by means of either cubic or quintic splines. Nonetheless, differently from previous approaches, the optimization cost functions are based on a virtual prototype of the system, which comprises behavioral models of power converter, controller, and electric motor coupled with the mechanical system. Results are then compared with experimental data obtained on a physical prototype. The comparison quantitatively shows that better-behaved PTP trajectories can be designed by including the dynamic contribution of each subsystem component.

Keywords: Electronic cams | high-speed machinery | intelligent manufacturing | mechatronic design methods | trajectory generation | virtual prototyping

Abstract: The selection of conceptual design alternatives is crucial in product development. This is due both to the fact that an iterative process is required to solve the problem and that communication among design team members should be optimized. In addition, several design constraints need to be respected. Although the literature offers several alternative selection methods, to date, only very few are currently being used in industry. A comparison of the various approaches would improve the knowledge transfer between design research and practice, helping practitioners to approach these decision support tools more effectively. This paper proposes a structured comparison of two decision support methods, namely the Fuzzy-Analytic Hierarchy Process and Pugh’s Controlled Convergence. From the literature debate regarding selection methods, four relevant criteria are identified: computational effort, suitability for the early design stages, suitability for group decision making, and ease of application. Finally a sensitivity analysis is proposed to test the robustness of each method. An industrial case study is described regarding an innovative and low-cost solution to increase the duration of heel tips in women’s shoes. The selection of conceptual design alternatives of the heel tip presents complex challenges because of the extremely difficult geometric constraints and demanding design criteria.

Keywords: Concept selection | Engineering design methods | Fuzzy-analytic hierarchy process | Pugh’s controlled convergence

Abstract: In the field of pharmaceutical processing, last generation automatic machines autonomously modify their behavior in order to achieve the best manufacturing quality and productivity despite ever changing process requirements. Mechatronics, as a synergistic integration of electro-mechanical equipment and software control logics, enables such adaptive self-optimizing behaviors. Unfortunately, due to the complex interactions between the different technologies, the final performance of these systems can be effectively validated and optimized only on a physical prototype, with limited possibilities to introduce possible design changes. Therefore, in order to enable validation/optimization of high performance machinery during engineering design stage, a mechatronic Virtual Prototyping (VP) technology is strongly needed. Within this context, the present work discusses a mechatronic VP method based on a Hardware-in-the-Loop, hybrid-process simulation approach, where interactive real-time simulations can effectively assess the real final performance under changing process scenarios. In particular, a case study concerning a high-speed automatic machines for pharmaceutical capsules filling is thoroughly discussed.

Keywords: Hardware-in-the-Loop | Intelligent Manufacturing | Mechatronic Design | Virtual Prototyping

Abstract: Simulation-Based-Training (SBT) allows to train the operators of complex machinery within a safe virtual environment by means of effective lifelike learning experiences. SBT has been efficiently used in medical, aerospace and military fields and it may provide a competitive advantage also for the training of operators in mechatronic plants. In fact, at the current state of the art, human-machine interaction still heavily impacts on the final performances of automated plants. Since the fast-evolving process dynamics of the machinery is controlled and supervised by complex software logics, the main challenge for effective and valid SBT concerns the development of a real-time simulation, where the control system responsiveness is fully reproduced. This paper deals with a novel SBT workbench used for steel plants operator training, discussing the real-time simulation architecture developed for the purpose. Following a hybrid process simulation approach, real-time control Hardware-In-the-Loop technology assures seamless and accurate reproduction of the real plant, also achieving the desired Man-in-the-Loop practice for the operator interaction. A conceptual architecture for a virtual interactive prototype is proposed, including controllers and interfaces for trainer and trainees. A case study on an electric arc furnace is implemented within a Virtual Commissioning tool, analyzing its capabilities and limitations.

Abstract: Multipurpose and programmable servo-actuated mechanisms may be envisaged as the key technology for increasing flexibility and re-configurability of modern automated machinery. Unfortunately, based on the current state-of-the-art, these mechatronic devices are extremely flexible but generally energy intensive, thus compromising the overall system sustainability. Nonetheless, the system power consumption can be partially reduced if energy optimality is introduced as a design goal along with the global productivity. Naturally, as a first step towards the practical implementation of any energy-optimality criterion, the end user should be capable of predicting the system power flow, including the major sources of energy loss. In this context, this paper firstly presents a reliable model of a servo-actuated mechanism accounting for linkage, electric motor and power converter behavior. Then, a novel identification method is discussed, which allows the separate determination of the models parameters by means of non-invasive experimental measures. The method is finally validated by comparing predicted and actual power flows in a simple mechatronic system, which is composed of a slider-crank mechanism directly coupled with a position-controlled permanent magnet synchronous motor.

Abstract: Dielectric Elastomers (DEs) are deformable dielectrics, which are currently used as active materials in mechatronic transducers, such as actuators, sensors and generators. Nonetheless, at the present state of the art, the industrial exploitation of DE-based devices is still hampered by the irregular electro-mechanical behavior of the employed materials, also due to the unpredictable effects of environmental changes in real world applications. In many cases, DE transducers are still developed via trial-and-error procedures rather than through a well-structured design practice, one reason being the lack of experimental data along with reliable constitutive parameters of many potential DE materials. Therefore, in order to provide the practicing engineer with some essential information, an open-access database for DE materials has been recently created and presented in [1]. Following the same direction, this paper addresses the temperature effect on the visco-hyperelastic behavior of two DE candidates, namely a natural rubber (ZRUNEK A1040) and a well-known acrylic elastomer (3M VHB 4905). Measurements are performed on pure shear specimens placed in a climactic chamber. Experimental stress-strain curves are then provided, which makes it possible to predict hyperelasticity, plasticity, viscosity, and Mullins effect as function of the environmental temperature. Properties of these commercial elastomeric membranes are finally entered in the database and made available to the research community.

Abstract: This paper quantitatively reports about potential energy savings on robotic assembly lines for the automotive industry. At first, a detailed system model is described, which improves previously published results by explicitly considering both manipulator and electrical drive dynamics. The model closely captures experimental data in terms of actuation torques and servodrive voltages, which are directly used to derive the plant input power. Two practical methods are then evaluated for reducing the overall energy consumption. The methods rely on: 1) implementation of energy-optimal trajectories obtained by means of time scaling, concerning the robots' motion from the last process point to the home positions and 2) reduction of energy consumption by releasing the actuator brakes earlier when the robots are kept stationary. Simulation results, based on the production timing characteristics measured at a real plant, clearly shows that the system energy consumption can be effectively reduced without negative effects on the production rate. © 2004-2012 IEEE.

Keywords: Energy efficient robotics | robotic manufacturing | trajectory planning | virtual prototyping

Abstract: Servo-actuated mechanisms are increasingly sub-stituting fully mechanical drives in order to increase flexibility and reconfigurability of modern automatic machines. The overall servomechanism performance, especially in the case of high-dynamic motions, is the direct consequence of several interacting factors, namely electric motor and linkage dynamics, controller efficacy, and requested motion law. In particular, Point-To-Point (PTP) trajectories are usually designed in order to comply with technological constraints, imposed by the required interaction with the handled product, and to maximize some optimality criterion such as, for instance, energy efficiency or limited actuation torques. In this context, the present paper proposes a novel method for generating either energy-optimal or torque-optimal PTP motions described by piecewise fifth-order polynomials. The optimization cost functions are based on a virtual prototype of the system, which comprises behavioral models of power converter, controller and electric motor coupled with the mechanical system. Results are then compared with experimental data obtained on a physical prototype. The comparison quantitatively shows that better-behaved PTP trajectories can be designed by including the dynamic contribution of each sub-system component. © 2013 IEEE.

Keywords: Servo-Actuated Mechanism | Trajectory Generation | Virtual Prototyping

Abstract: Fixture systems have a great importance in modern manufacturing and assembly because of the high number of scenarios in which they are used. Fixture design is a complex task since the system effectiveness depends both on position and type of locators. Several authors deal with the problem of determine the most suitable design for fixture systems but their investigation is commonly limited to the evaluation of the effects due to the locators' position. In the present work a design method is proposed to evaluate the fixture systems considering also the locators' type. Since it is possible to model the fixtures as multi-performance systems, the comparison is performed by introducing appropriate sensitivity indexes. The effectiveness of the design method is proved through the application to an automotive case study. © (2013) Trans Tech Publications, Switzerland.

Keywords: Automotive | Design for manufacturing | Fixture system | Tolerance analysis

Abstract: This paper reports about the design and modeling process of high performance servo-actuated mechanisms for automatic machines.Besides being a delicate and time consuming process, coupled simulations based on virtual prototyping finally offer the chance to integrate engineering methods proper of control system engineering and mechanical design. In particular, the main target of this work isto investigate how different virtual prototyping approaches, each havingincreasing level of detail, can contribute to the appropriate prediction of the expected machine performance.These results are then compared with experimental data obtained on a real servomechanism prototype. The comparison quantitatively demonstrate the improvement on torque prediction and position error reduction when detailed models of the controller and the electric motor dynamics are coupled with the mechanical system model. © (2013) Trans Tech Publications, Switzerland.

Keywords: Co-simulation | Digital product design | Integrated mechatronic design | Virtual prototyping

Abstract: Machining using industrial robots is currently limited to applications with low geometrical accuracies and soft materials due to weaknesses of the robot structure, insufficient controller performance and the lack of suitable software tools. This paper proposes a modular approach to overcome these obstacles, applied both during program generation (offline) and execution (online). Offline predictive machining errors compensation is achieved by means of an innovative programming system, based on kinematic and dynamic robot models. Realtime adaptive machining error compensation is also provided by sensing the real robot positions with an innovative tracking system and corrective feedback to both the robot and an additional high dynamic compensation mechanism on piezo-actuator basis. Due to the modularity of the approach, an individual setup can be compiled for each actual use-case. Final experimental validation of the components is currently ongoing in multiple robot cells, covering several application areas as aerospace, automotive or mould construction. © Springer-Verlag Berlin Heidelberg 2013.

Keywords: 3D-piezo-actuator compensation mechanism | Engineering methods | Robotic machining

Abstract: Industrial robotics provides high flexibility and reconfigurability, cost effectiveness and user friendly programming for many applications but still lacks in accuracy. An effective workcell calibration reduces the errors in robotic manufacturing and contributes to extend the use of industrial robots to perform high quality finishing of complex parts in the aerospace industry. A novel workcell calibration method is embedded in an integrated design framework for an in-depth exploitation of CAD-based simulation and offline programming. The method is composed of two steps: a first offline calibration of the workpiece-independent elements in the workcell layout and a final automated online calibration of workpiece-dependent elements. The method is finally applied to a robotic workcell for finishing aluminum housings of aerospace gear transmissions, characterized by complex and non-repetitive shapes, and by severe dimensional and geometrical accuracy demands. Experimental results demonstrate enhanced performances of the robotic workcell and improved final quality of the housings. © Springer-Verlag Berlin Heidelberg 2013.

Keywords: Aerospace industry | Industrial robotics | Integrated design | Workcell calibration

Abstract: Deburring of aerospace components is a complex task in case of large single pieces designed and optimized to deliver many mechanical functions. A constant high quality requires accurate 3D surface contouring operations with engineered tool compliance and cutting power. Moreover, aeronautic cast part production is characterized by small lot sizes with high variability of geometries and defects. Despite robots are conceived to provide the necessary flexibility, reconfigurability and efficiency, most robotic workcells are very limited by too long programming and setup times, especially at changeover. The paper reports a design method dealing with the integrated development of process and production system, and analyzes and compares a CAD-based and a digitizer-based offline programming strategy. The deburring of gear transmission housings for aerospace applications serves as a severe test field. The strategies are compared by the involved costs and times, learning easiness, production downtimes and machining accuracy. The results show how the reconfigurability of the system together with the exploitation of offline programming tools improves the robotic deburring process. © Springer-Verlag Berlin Heidelberg 2013.

Keywords: CAD-based tools | Digitizers | Industrial robotics | Integrated design | Offline programming

Abstract: The interest in novel methods and tools for opt imizing the energy consumption in robotic systems is cur- rently increasing. From an industrial point of view,it is desirable to develop energy saving strategies also applicable to established manufacturing systems with no need for either hardware substitu tion or further investme nts. Within this scenario,the present paper reports amethod for reducing the total energy con- sumption of pick-and-place manipulators for given TCP position profiles.Firstly,electromechanical mod- els of both serial and parallel manipulators are derive d.Then,the energy-optimal trajectories are calculated, by means of constant time scaling,starting from pre-scheduled trajectories comp atible with the actuation limits. In this manner,the robot work cycle can be energetically optimized also when the TCP position profiles have been already definedon the basis of technological constraints and/or design choices aimed at guarante eing manufacturing process efficacy/robustness.The effectiveness of the pro- posed procedure is finallyevaluated on two simulation case studies. Copyright © 2013 Published by Elsevier Ltd. All rights reserved.

Keywords: Electromechanical modeling | Energy efficiency | Robotic manufacturing | Virtual prototyping

Abstract: This paper quantitatively reports about potential energy savings on robotic assembly lines for the automotive industry. The key aspect of the proposed approach is that both cell production rate and robot hardware limitations are considered as strict constraints, so that no plant revision is needed. The methodology relies on: a) calculation of energy-optimal trajectories, by means of time scaling, concerning the robots' motion from the last process point to the home positions; b) reduction of the energy consumption via earlier release of the actuator brake when the robots are kept stationary. Simulation results are presented, which are based on the production timing characteristics measured on a real plant. © 2012 IEEE.

Keywords: Energy Efficiency | Industrial Robots | Production Planning | Trajectory Scaling

Abstract: Changeability accomplishes the engineering design of competitive sustainable manufacturing systems, considered as industrial products characterized by inherent life cycle. Main drivers for changeability are manufacturing system reconfigurability and hybridization. A Hybrid Reconfigurable System (H-RS) is characterized by the coexistence and cooperation of industrial robots and skilled human workers to perform complex tasks within a common reconfigurable production environment. H-RSs rise use-productivity along their total system life cycle, fostering the evaluation and implementation of feasible and innovative technologies, and increasing the utilization ratio and the multiple use-or re-use-of resources. The paper proposes an engineering method which aims at enhancing changeability in H-RSs through the application of a multi level reconfigurability approach within a digital environment. The method includes the advanced design and modeling of digital devices which embed mechanics, electronics, control logic and software code. Advanced models are exploited to analyze the system performance in the system domain of changes and to realize an effective human training. An industrial case study describes the application of the method to the design of a hybrid reconfigurable workcell for manufacturing and assembly of top class car chassis. © 2012 Springer-Verlag.

Keywords: Automotive | Changeability | Digital environment | Hybrid Reconfigurable System

Abstract: Reduction of energy consumption is important for reaching a sustainable future. This paper presents a novel method for optimizing the energy consumption of robotic manufacturing systems. The method embeds detailed evaluations of robots' energy consumptions into a scheduling model of the overall system. The energy consumption for each operation is modeled and parameterized as function of the operation execution time, and the energy-optimal schedule is derived by solving a mixed-integer nonlinear programming problem. The objective function for the optimization problem is then the total energy consumption for the overall system. A case study of a sample robotic manufacturing system and an experiment on an industrial robot are presented. They show that there exists a real possibility for a significant reduction of the energy consumption in comparison to state-of-the-art scheduling approaches. © 2012 IEEE.

Keywords: Energy optimization | mathematical programming | robot cells | scheduling and coordination | system modeling and simulation

Abstract: Engineering changeability-oriented and cost-driven approaches are needed by enterprises to design and optimize manufacturing and assembly systems for the demanding production requirements of the present industrial scenario. The integrated design of Reconfigurable Systems addresses tailored flexibility through modularity, integrability of resources, product and process customization, and system convertibility and diagnosability. The cooperation of robot and humans in hybrid environments offers a good trade-off between changeability, high quality and low costs, by exploiting the human dexterity and cognitive proactivity, together with robotic accuracy and performances. Virtual prototyping methods and digital manufacturing solutions are now mature and effective enough to play a strategic role within the hybrid reconfigurable system (H-RS) design and optimization process. The present research work proposes an engineering method to design and optimize H-RSs, by using virtual prototyping and digital manufacturing as a strategic support for the analysis and synthesis of the technical solutions, especially those related to human-robot cooperation. An industrial case study on a hybrid reconfigurable assembly system of a top class car aluminum chassis is finally presented. © 2011 Springer-Verlag.

Keywords: Automotive industry | Digital manufacturing | Hybrid reconfigurable system | Virtual prototyping

Abstract: The interest in novel engineering methods and tools for optimizing the energy consumption in robotic systems is currently increasing. In particular, from an industry point of view, it is desirable to develop energy saving strategies applicable also to established manufacturing systems, being liable of small possibilities for adjustments. Within this scenario, an engineering method is reported for reducing the total energy consumption of pick-and-place manipulators for given end-effector trajectory. Firstly, an electromechanical model of parallel/serial manipulators is derived. Then, an energy-optimal trajectory is calculated, by means of time scaling, starting from a pre-scheduled trajectory performed at maximum speed (i.e. compatible with actuators limitations). A simulation case study finally shows the effectiveness of the proposed procedure. © 2011 IEEE.

Keywords: energy efficiency | Pick-and-place manipulators

Abstract: The development of safe, energy efficient mechatronic systems is currently changing standard paradigms in the design and control of industrial manipulators. In particular, most optimization strategies require the improvement or the substitution of different system components. On the other hand, from an industry point of view, it would be desirable to develop energy saving methods applicable also to established manufacturing systems being liable of small possibilities for adjustments. Within this scenario, an engineering method is reported for optimizing the energy consumption of serial manipulators for a given operation. An object-oriented modeling technique, based on bond graph, is used to derive the robot electromechanical dynamics. The system power flow is then highlighted and parameterized as a function of the total execution times. Finally, a case study is reported show- ing the possibility to reduce the operation energy consumption when allowed by scheduling or manufacturing constraints. Copyright © 2011 by ASME.

Abstract: Reduction of energy consumption is important for reaching a sustainable future. This paper presents a novel method for optimizing the energy consumption of robotic manufacturing systems. The method embeds detailed evaluations of robots' energy consumptions into a scheduling model of the overall system. The energy consumption for each operation is modelled and parameterized as function of the operation execution time, and the energy-optimal schedule is derived by solving a mixed-integer nonlinear programming problem. The objective function for the optimization problem is then the total energy consumption for the overall system. A case study of a sample robotic manufacturing system is presented. It shows that there exists a possibility for a significant reduction of the energy consumption, in comparison to state-of-the-art scheduling approaches. © 2010 IEEE.

Abstract: A fast and interactive implementation for camera pose registration and 3D point reconstruction over a physical surface is described in this paper. The method (called SRE-Smart Reverse Engineering) extracts from a continuous image streaming, provided by a single camera moving around a real object, a point cloud and the camera's spatial trajectory. The whole per frame procedure follows three steps: camera calibration, camera registration, bundle adjustment and 3D point calculation. Camera calibration task was performed using a traditional approach based on 2-D structured pattern, while the Optical Flow approach and the Lucas-Kanade algorithm was adopted for feature detection and tracking. Camera registration problem was then solved thanks to the Essential Matrix definition. Finally a fast Bundle Adjustment was performed through the Levenberg-Marquardt algorithm to achieve the best trade-off between 3D structure and camera variations. Exploiting a PC and a commercial webcam, an experimental validation was done in order to verify precision in 3D data reconstruction and speed. Practical tests helped also to tune up several optimization parameters used to improve efficiency of most CPU time consuming algorithms, like Optical Flow and Bundle Adjustment. The method showed robust results in 3D reconstruction and very good performance in real-time applications. © 2010 Springer-Verlag.

Keywords: 3D vision | Interactive modeling | Reverse engineering | Shape reconstruction | Surface remodeling

Abstract: Adaptive manufacturing systems achieve intelligence and adaptation capabilities through the close interaction between mechanics, electronics, control and software engineering. Mechatronic design of intelligent manufacturing behaviours is of paramount importance for the final performances of complex systems and requires deep integration between mechanical and control engineering. Virtual Commissioning environments offer engineers new opportunities for the design of complex intelligent behaviours and for the enhancement of the performance of adaptive manufacturing systems. This paper discloses a systematic design method focused on interdisciplinary behavioural simulations: Virtual Commissioning tools are used to virtually explore new solution spaces for an effective mechatronic optimization. The results, achieved by applying the method in reengineering a module of an automotive sensor manufacturing line, are finally presented. © 2009 Springer-Verlag.

Keywords: Computer aided engineering | Mechatronic design | Virtual commissioning

Abstract: Direct type [1] Tire Monitoring Systems supervise tire internal inflating pressure. The authors previously proved that Tire Monitoring must be focused on the tire (i.e.: vehicle) dynamic behaviour [2]: the real aim of the supervising action. In this case, even the external absolute pressure must be taken into account. NHTSA studies showed improper warnings must be avoided in order to keep the driver confidence with the system; internal temperature decrease is the Tire Monitoring Systems' main cause of improper warnings. A new approach for optimal Tire Monitoring Systems temperature compensation related to external environmental temperature, able to avoid improper warnings, will be presented. Copyright © 2004 SAE International.

Abstract: Monitoring tires working conditions has proved to be very important for best aircraft ground performances. Thus, to prevent safety risks it is necessary to recognize all the parameters really affecting tires dynamic behaviour and study a proper supervising strategy, able to guarantee an easy and effective security action. It will be proved that measuring tire internal gas pressure (even with internal temperature compensation, then measuring the total internal gas mass) it is not possible to monitor accurately the tire dynamic behaviour. In this paper a new approach to design a new generation of tires monitoring system will be presented. Copyright © 2003 SAE International.