Virtual prototyping and digital twin

In the era of Industry 4.0, several advantages for industries come by the implementation of new technologies that play a key role for improving production processes, focusing on working times, product quality, accuracy of operations and other important parameters of the production systems. In order to evaluate these parameters, simulation may be used as a tool to verify (i) the improvement adopted on existing production lines or (ii) the design solutions adopted for a new line, optimizing the processes. The aim of this paper is to investigate the possibility to assess the before said parameters in a specific case study by implementing a Discrete Event Simulation (DES). The study concerns two consecutive workplaces of an automotive assembly line in which three workers are involved in assembly activities. The results demonstrated that the Digital Manufacturing (DM) approach and simulation may be used for verifying the performances of the line, thanks to the evaluation of important parameters, such as the Overall Equipment Effectiveness (OEE).

Keywords: Overall Equipment Effectiveness , Simulation , Work measurement

Human and robot collaboration represents an interesting development direction for traditional industrial robotic solutions. Especially for those cases where the operations are difficult to automate or burdensome for manual execution, the mutual exchange of human sensitivity and robot repeatability represents an effective approach. Nevertheless, industrial robots are poorly involved for collaborative tasks since specific safety countermeasures are required to avoid all the potential hazards. Consequently, the design and assessment of safety solutions represents a fundamental phase to estimate feasibility of industrial collaborative solutions. The presented work proposes a computer-aided approach to identify, assess and optimize the safety systems that enables the collaborative usage of industrial robots. It exploits the capabilities of virtual controller-based offline programming packages to design in advance the safety countermeasures. An initial consistency test validates the response of the selected tool with respect to the safety functionalities. Subsequently, a virtual replica of a potential industrial collaborative solution has been developed. As a result, it has been possible to mimic the behaviour of such a system with respect to Speed and Separation Monitoring collaborative method.

Keywords: Computer-aided assessment , Human-robot collaboration , Indutrial robots , Safey countermeasures , Speed and separation monitoring

Continuous innovation in the field of high-end motor vehicle chassis demands optimization of the weight/stiffness ratio and to achieve high quality standards. The use of light materials, such as aluminum alloys, is therefore increasingly common in the design of the chassis, whose assembly process represents a technological challenge. Welding joining processes, and in particular robot-based welding, are widely used in automotive field despite causing distortions. To predict these deformations, finite element analyzes are performed, in particular thermo-elasto-plastic simulations, which are able to satisfactorily replicate the behavior of residual stresses and strains after cooling. However, such analyzes are computationally expensive making their application difficult to complex structures. This work would investigate an alternative solution to predict distortions that effectively returns the behavior of welded assemblies. A CAE-based model for TEP analysis of welded joints is proposed. As a case study, the T-welded junction between two aluminum alloy plates (T-Joint) was considered. The model is validated by a preliminary experimental campaign.

Keywords: CAE-based model , TEP analysis , Termo-elasto-plastic model , Welding process

Predictive Maintenance (PdM) is a prominent strategy comprising all the operational techniques and actions required to ensure machine availability and to prevent a machine-down failure. One of the main challenges of PdM is to design and develop an embedded smart system to monitor and predict the health status of the machine. In this work, we use a data-driven approach based on machine learning applied to woodworking industrial machines for a major woodworking Italian corporation. Predicted failures probabilities are calculated through tree-based classification models (Gradient Boosting, Random Forest and Extreme Gradient Boosting) and calculated as the temporal evolution of event data. This is achieved by applying temporal feature engineering techniques and training an ensemble of classification algorithms to predict Remaining Useful Lifetime (RUL) of woodworking machines. The effectiveness of the proposed method is showed by testing an independent sample of additional woodworking machines without presenting machine down. The Gradient Boosting model achieved accuracy, recall, and precision of 98.9%, 99.6%, and 99.1%. Our predictive maintenance approach deployed on a Big Data framework allows screening simultaneously multiple connected machines by learning from terabytes of log data. The target prediction provides salient information which can be adopted within the maintenance management practice.

Keywords: Big data platform , Feature engineering , Machine learning , Predictive maintenance , Remaining useful lifetime

Intramedullary nails constitute a viable alternative to extramedullary fixation devices; their use is growing in recent years, especially with reference to self-locking nails. Different designs are available, and it is not trivial to foresee the respective in vivo performances and to provide clinical indications in relation to the type of bone and fracture. In this work a numerical methodology was set up and validated in order to compare the mechanical behavior of two new nailing device concepts with one already used in clinic. In detail, three different nails were studied: (1) the Marchetti-Vicenzi's nail (MV1), (2) a revised concept of this device (MV2), and (3) a new Terzini-Putame's nail (TP) concept. Firstly, the mechanical behavior of the MV1 device was assessed through experimental loading tests employing a 3D-printed component aimed at reproducing the bone geometry inside which the device is implanted. In the next step, the respective numerical model was created, based on a multibody approach including flexible parts, and this model was validated against the previously obtained experimental results. Finally, numerical models of the MV2 and TP concepts were implemented and compared with the MV1 nail, focusing the attention on the response of all devices to compression, tension, bending, and torsion. A stability index (SI) was defined to quantify the mechanical stability provided to the nail-bone assembly by the elastic self-locking mechanism for the various loading conditions. In addition, results in terms of nail-bone assembly stiffness, computed from force/moment vs. displacement/rotation curves, were presented and discussed. Findings revealed that numerical models were able to provide good estimates of load vs. displacement curves. The TP nail concept proved to be able to generate a significantly higher SI (27 N for MV1 vs. 380 N for TP) and a greater stiffening action (up to a stiffness difference for bending load that ranges from 370 Nmm/° for MV1 to 1,532 Nmm/° for TP) than the other two devices which showed similar performances. On the whole, a demonstration was given of information which can be obtained from numerical simulations of expandable fixation devices.

Keywords: biomechanical stability , experimental tests , flexible bodies , intramedullary nails , Marchetti-Vicenzi nail , multibody analysis , stiffness

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

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

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)

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. © 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.

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

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

In the last past years, computer-Aided technologies to improve existing products by widening the design space have been largely investigated. Topology optimization and generative design are two of the most representative technologies of such kind. This paper aims at investigating the use of generative design and topology optimization techniques to improve products whose design has not changed radically over the years. The product under investigation is a disk brake floating caliper that is the most common solution for commercial vehicles. In general, increasing the stiffness of the floating caliper while keeping its weight under control is desirable both from performance and fuel consumption point of view. The solution here proposed aims at exploiting two new ways to approach the engineering design process and evaluate which one is more suitable for problems of this kind. Starting from the original carrier shape, acquired with laser scanning, the two technologies have been applied on the same initial conditions. The initial design space volume corresponds to the acquired shape, the loads and the constraints for the simulation have been drawn reasonably to resemble the actual operating conditions. Keeping the input parameters constants, two different off-The-shelf software packages have been used to perform the computation and with the objective of maximizing the stiffness of the carrier while reducing its mass. The comparison and the improvements on the final designs have been drawn taken as reference to the original caliper..

Main target of this paper is to describe the conceptual design and the virtual prototyping phases of a new detector, named Crystal Eye, aimed at the exploration of the electromagnetic counterpart of the gravitational wave events. Such events generated by neutron stars collision (or mergers) are associated with γ-ray bursts. With its characteristics, Crystal Eye will provide the continuous exploration and monitoring of the Universe after a Gravitational Wave event with a better resolution than that of other detectors such as the Fermi Gamma-ray Burst Monitor (GBM). Thanks to its large field of view and its design, it has the potentiality to be the trigger for those present X-ray astronomy missions (Chandra, Swift, Integral XMM Newton) that are based on high angular resolution pointing experiment but that have unfortunately a very small field of view. An intense brainstorming phase, involving a team of physicians and engineers for the generation of concepts, started the design process. So, many preliminary sketches and CAD models were realized to well identify the main requirements of the new detector. Afterwards, considering the features and the constraints of the project, a refinement of the possible solutions among all the alternatives thought was performed, and three virtual prototypes were selected according to the Multi-Voting Method. Lastly, the AHP (Analytic Hierarchy Process) Multi Criteria decision making approach was considered to designate the best concept.

Keywords: AHP , Concept Design , Detector , Gravitational Wave , Mechanical Design , Multi-Voting method , X-rays

Introduction: Miniscrew-assisted rapid palatal expansion (MARPE) appliances utilize the skeletal anchorage to expand the maxilla. One type of MARPE device is the Maxillary Skeletal Expander (MSE), which presents four micro-implants with bicortical engagement of the palatal vault and nasal floor. MSE positioning is traditionally planned using dental stone models and 2D headfilms. This approach presents some critical issues, such as the inability to identify the MSE position relative to skeletal structures, and the potential risk of damaging anatomical structures. Methods: A novel methodology has been developed to plan MSE position using the digital model of dental arches and cone-beam computed tomography (CBCT). A virtual model of MSE appliance with the four micro-implants was created. After virtual planning, a positioning guide is virtually designed, 3D printed, and utilized to model and weld the MSE supporting arms to the molar bands. The expansion device is then cemented in the patient oral cavity and micro-implants inserted. A clinical case of a 12.9-year-old female patient presenting a Class III malocclusion with transverse and sagittal maxillary deficiency is reported. Results: The midpalatal suture was opened with a split of 3.06 mm and 2.8 mm at the anterior and posterior nasal spine, respectively. After facemask therapy, the sagittal skeletal relationship was improved, as shown by the increase in ANB, A-Na perpendicular and Wits cephalometric parameters, and the mandibular plane rotated 1.6° clockwise. Conclusion: The proposed digital methodology represents an advancement in the planning of MSE positioning, compared to the traditional approach. By evaluating the bone morphol-ogy of the palate and midface on patient CBCT, the placement of MSE is improved regarding the biomechanics of maxillary expansion and the bone thickness at micro-implants insertion sites. In the present case report, the digital planning was associated with a positive outcome of maxillary expansion and protraction in safety conditions.

Keywords: CBCT , CBDP , Cephalometrics-based digital planning , MARPE , Miniscrew-assisted rapid palatal expansion , MSE , TAD , Virtual planning , Workflow

The electrification of utility vehicles represents a promising solution to reduce the emissions in the urban context. Differently from traditional vehicles, they operate intermittently and generally follow routine driving cycles. In this paper, we model a 15-kW electric utility vehicle, adopting a backward-looking approach, widely used in literature to estimate the range of electric cars. The model requires a limited number of data, either supplied by the vehicle manufacturer or found in literature, as in case of the induction motor/generator efficiency and of the battery Peukert coefficient. The model can be used to assess the possibility of the vehicle to complete an assigned mission, as well as to optimize the vehicle's design and architecture. The model is validated on GPS data obtained through an experimental campaign where the electric utility vehicle was driven to depletion considering different routes, including the effect of slopes. A satisfactory correspondence with the experimental data was observed with maximum difference in the simulated average energy consumption lower than about 8%. Results of the simulations show that the range of the electric utility vehicle is about 110 km on urban flat cycle while it significantly reduces when slopes are included in portions of the routes.

The main sources of sound emitted by vehicles are the engine and the rolling noise produced by the tires. In case agricultural tractors are considered, the engine and the transmission are responsible of the main emissions since they often work in the fields on soft ground at low speeds. This work focuses on the combined acoustic and mechanical development of a new exhaust system for an existing agricultural tractor, with the aim of providing a product with improved acoustic performances and a neater design. The host vehicle is equipped with a 300 hp diesel engine which can be particularly noisy at low rpm, with a further constraint being the “under the bonnet” available volume to fit the system into. The existing exhaust system is the baseline for the engineering process. The acoustic design is carried out by a 1D simulation software based on an electro-acoustic analogy, while the design modelling is performed by using Solidworks® 3D CAD. After the design stage a prototype has been manufactured and tested at the MWL/KTH laboratory. The engineering process gave the product a cleaner design and allowed to identify feasible solutions ensuring increased sound attenuation performances.

Introduction of collision models aided surgeons to plan their resection of the femoral and acetabular impinging deformities. Their application on the hip joint is particularly interesting in association with hip arthroscopy because with technique the vision is limited and identifying friction's zones is not easy. Although their large diffusion in the market, they still presents several limits. First, the 3D reconstruction has been used only in the preoperatory phase. Its use inside the operatory room is still not available. Furthermore the actual software lack of a pure automatized program to create the 3D model of the hip. Second, nowadays collision model's software separate and study only the bony part of the hip, erasing from the 3D reconstruction soft tissues. Third, the programs currently developed use statistical data as reference to 3d virtual models and the motion between the hip's bones. They base the motion analysis on the comparison between data extrapolated from the healthy population and data from the patient exam, consequently image processing may be inaccurate. Although according to our opinion collision model are useful even with their actual limits, in this chapter we describe the limits of the actual software and their potential development. © 2020 by Nova Science Publishers, Inc. All rights reserved.

Objectives: To investigate the influence of different resin composite and glass ionomer cement material combinations in a “bi-layer” versus a “single-layer” adhesive technique for class I cavity restorations in molars using numerical finite element analysis (FEA). Materials and Methods: Three virtual restored lower molar models with class I cavities 4 mm deep were created from a sound molar CAD model. A combination of an adhesive and flowable composite with bulk fill composite (model A), of a glass ionomer cement with bulk fill composite (model B) and of an adhesive with bulk fill composite (model C), were considered. Starting from CAD models, 3D-finite element (FE) models were created and analyzed. Solid food was modeled on the occlusal surface and slide-type contact elements were used between tooth surface and food. Polymerization shrinkage was simulated for the composite materials. Physiological masticatory loads were applied to these systems combined with shrinkage. Static linear analyses were carried out. The maximum normal stress criterion was adopted as a measure of potential damage. Results: All models exhibited high stresses principally located along the tooth tissues–restoration interfaces. All models showed a similar stress trend along enamel–restoration interface, where stresses up to 22 MPa and 19 MPa was recorded in the enamel and restoration, respectively. A and C models showed a similar stress trend along the dentin-restoration interface with a lower stress level in model A, where stresses up to 11.5 MPa and 7.5 MPa were recorded in the dentin and restoration, respectively, whereas stresses of 17 MPa and 9 MPa were detected for model C. In contrast to A and C models, the model B showed a reduced stress level in dentin, in the lower restoration layer and no stress on the cavity floor. Significance: FE analysis supported the positive effect of a “bi-layer” restorative technique in a 4 mm deep class I cavities in lower molars versus “single-layer” bulk fill composite technique.

Keywords: 3D-finite element analysis , GIC , Resin composites , Shrinkage , Stress

Purpose: To examine the influence of different bulk and block composite and flowable and glass-ionomer material combinations in a multi-layer technique and in a unique technique, in deep Class I dental restorations. Methods: 3D CAD of the sound tooth were built-up from a CT scan dataset using reverse engineering techniques. Four restored tooth models with Class I cavity were virtually created from a CAD model of a sound tooth. 3D-finite element (FE) models were created and analyzed starting from CAD models. Model A with flowable resin composite restoring the lower layer and bulk-fill resin composite restoring the upper layer, model B with glass-ionomer cement (GIC) restoring the lower layer and bulk-fill resin composite restoring the upper layer, model C with block composite as the only restoring material and model D with bulk-fill resin composite as the only restoring material. Polymerization shrinkage was simulated with the thermal expansion approach. Physiologic masticatory loads were applied in combination with shrinkage effect. Nodal displacements on the lower surfaces of FE models were constrained in all directions. Static linear analyses were carried out. The maximum normal stress criterion was used to assess the influence of each factor. Results: Considering direct restoring techniques, models A, B and D exhibited a high stress gradient at the tooth/restorative material interface. Models A and D showed a similar stress trend along the cavity wall where a similar stress trend was recorded in the dentin and enamel. Model B showed a similar stress trend along enamel/restoration interface but a very low stress gradient along the dentin/restoration interface. Model C with a restoring block composite material showed a better response, with the lowest stress gradient at the dentin, filling block composite and enamel sides.

Meeting the demands of Industry 4.0 and Digital Manufacturing requires a transformative framework for achieving crucial manufacturing goals such as zero-defect production or right-first-time development. In essence, this necessitates the development of self-sustainable manufacturing systems which can simultaneously adapt to high product variety and system responsiveness; and remain resilient by rapidly recovering from faulty stages at the minimum cost. A Closed-Loop In-Process (CLIP) quality control framework is envisaged with the aim to correct and prevent the occurrence of quality defects, by fusing sensing techniques, data analytics and predictive engineering simulations. Although the development and integration of distributed sensors and big data management solutions, the flawless introduction of CLIP solutions is hindered specifically with respect to acquiring and providing in-process data streams at the required level of: (1) veracity (trustworthiness of the data); (2) variety (types of data generated in-process); (3) volume (amount of data generated in-process); and, (4) velocity (speed at which new data is generated in-process) as dictated by rapid introduction and evolution of coupled system requirements. This paper illustrates the concept of the CLIP methodology in the context of assembly systems and highlights the need for a holistic approach for data gathering, monitoring and in-process control. The methodology hinges on the concept of “Multi-Wave Light Technology” and envisages the potential use of light-based technology, thereby providing an unprecedented opportunity to enable in-process control with multiple and competing requirements. The proposed research methodology is presented and validated using the development of new joining process for battery busbar assembly for electric vehicles with remote laser welding.

Keywords: Battery busbar assembly , Closed-loop in-process quality control , Multi-level requirements , Multi-wave light technology , Remote laser welding