Geometric modeling and processing

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

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

Assembly sequence planning starting from CAD models turned out to be a relevant task in the industrial manufacturing field. To have a successful assembly sequence, the relations between the assembly's parts and the possible interferences during the assembly operations deserve to be investigated. In particular, the collision analysis is the phase in which the movement of each part along some directions is evaluated to assess if it is obstructed by any of the other parts, and according to which the precedence matrix is computed. A lot of work has been done to address the problem, however, existing algorithms need to be improved yet. Among the open issues, the following three result to be the most challenging: the combinatorial explosion of the problem complexity, the limited choice of the assembly directions, and the engineering meaning of parts that is not taken into account, or it is manually given in input by experts. In this paper, an automatic assembly sequence planning approach is introduced. The focus is on the collision detection and precedence analysis for engineering meaningful subassemblies, namely the axisymmetric. Information automatically extracted relying on geometric processing and engineering knowledge, such as parts features and semantic interpretation of mechanical components, is first exploited to identify the subassemblies and, then, to choose the feasible assembly direction, as well as to treat fasteners and deformable parts in a more realistic way. An industrial CAD model of a gearbox is selected as case study to illustrate the approach, also emphasizing the importance of axisymmetric subassemblies.

Keywords: Assembly sequence planning , CAD model processing , Collision analysis , Precedence matrix

The Heavy Ion Therapy Research Integration plus (HITRIplus) is an European project that aims to integrate and propel research and technologies related to cancer treatment with heavy ion beams. Among the ambitious goals of the project, a specific work package includes the design of a gantry for carbon ions, based on superconducting magnets. The first milestone to achieve is the choice of the fundamental gantry parameters, namely the beam optics layout, the superconducting magnet technology, and the main user requirements. Starting from a reference 3 T design, the collaboration widely explored dozens of possible gantry configurations at 4 T, aiming to find the best compromise in terms of footprint, capital cost, and required R&D. We present here a summary of these configurations, underlying the initial correlation between the beam optics, the mechanics and the main superconducting dipoles design: the bending field (up to 4 T), combined function features (integrated quadrupoles), magnet aperture (up to 90 mm), and angular length (30° – 45°). The resulting main parameters are then listed, compared, and used to drive the choice of the best gantry layout to be developed in HITRIplus.

Keywords: Heavy ions , Ion beams

Indeterminate lung nodules detected on CT are common findings in the clinical practice, and the correct assessment of their size is critical for patient evaluation and management. We compared the stability of three definitions of nodule diameter (Feret's mean diameter, Martin's mean diameter and area-equivalent diameter) to inter-observer variability on a population of 336 solid nodules from 207 subjects. We found that inter-observer agreement was highest with Martin's mean diameter (intra-class correlation coefficient = 0.977, 95% Confidence interval = 0.977–0.978), followed by area-equivalent diameter (0.972, 0.971–0.973) and Feret's mean diameter (0.965, 0.964–0.966). The differences were statistically significant. In conclusion, although all the three diameter definitions achieved very good inter-observer agreement (ICC > 0.96), Martin's mean diameter was significantly better than the others. Future guidelines may consider adopting Martin's mean diameter as an alternative to the currently used Feret's (caliper) diameter for assessing the size of lung nodules on CT.

Keywords: Computed tomography , Inter-observer variability , Lung nodules , Size assessment

Additive Manufacturing has enabled the design of complex components in several technical fields. Considering turbomachinery components, additive manufacturing has unlocked the achievement of significant performances for dynamic rotoring components. The application of topology optimization methods is one of the main factors accelerating the technological development of this sector. This paper presents a procedure for the optimization of static turbomachinery components. The framework proposed compares the results obtained by introducing a lattice structure and a solid optimized shape. The procedure is presented with reference to a specific case study. To validate the proposed framework, the complete re-design of a thrust collar of a major Italian-based Oil&Gas company is carried out, demonstrating that the re-thinking of the component in terms of Topology Optimization is a straightforward approach to increase the overall performance of the produced part

Keywords: dynamic optimization , thrust washer , Topology optimization , turbomachinery

The largest contribution of electricity production comes from conventional sources including coal and oil that pollute the environment. Renewable energy sources, including solar energy, wind energy and energy storage in batteries, are expected to play a progressively central role in meeting future energy needs in all sectors, largely responding to the increasing demand for energy. In particular, the use of solar energy will be considered as the main solution to global climate change and fossil fuel emissions. Although today's photovoltaic panels have an average lifespan of 25 years, their disposal is a cause for concern when photovoltaic technology is evaluated from the perspective of comprehensive life cycle analysis and End-of-Life management (EoL). We therefore need some innovative solutions that can reduce emissions of pollutants as a result of the recycling of solar panels that no longer work. This manuscript reports some of the most current efficient and effective photovoltaic (PV) panel recycling solutions and the foreseeable developments for such recycling.

Keywords: EcoDesign , End-of-life management , Photovoltaic panels , Renewable resources , Sustainability

This paper presents a collaborative platform developed to allow the communication between surgeons and engineers in the process of designing patient-specific surgical instruments. To date, only a few applications are available to collaboratively create surgical instruments from medical 3D models, mostly dedicated to expert CAD modelers. This makes the preoperative planning process time-consuming and inefficient limiting the usability of applications and making planning difficult and inaccurate. Accordingly, we propose a solution in the form of a web-based, interactive, extendable, 3D navigation and manipulation application, called Precise, which does not require client installation. Precise is a lightweight, high-performance application built to provide easy-to-use, powerful, on-demand visualization and manipulation of 3D images, implemented using open-source libraries.

Keywords: 3D manipulation , Medical application , Rapid prototyping , Surgical planning

Background and objective: The ability to accomplish a consistent restoration of a missing or deformed anatomical area is a fundamental step for defining a custom implant, especially in the maxillofacial and cranial reconstruction where the aesthetical aspect is crucial for a successful surgical outcome. At the same time, this task is also the most difficult, time-consuming, and complicated across the whole reconstruction process. This is mostly due to the high geometric complexity of the anatomical structures, insufficient references, and significant interindividual anatomical heterogeneity. Numerous solutions, specifically for the neurocranium, have been put forward in the scientific literature to address the reconstruction issue, but none of them has yet been persuasive enough to guarantee an easily automatable approach with a consistent shape reconstruction. Methods: This work aims to present a novel reconstruction method (named HyM3D) for the automatic restoration of the exocranial surface by ensuring both the symmetry of the resulting skull and the continuity between the reconstructive patch and the surrounding bone. To achieve this goal, the strengths of the Template-based methods are exploited to provide knowledge of the missing or deformed region and to guide a subsequent Surface Interpolation-based algorithm. HyM3D is an improved version of a methodology presented by the authors in a previous publication for the restoration of unilateral defects. Differently from the first version, the novel procedure applies to all kinds of cranial defects, whether they are unilateral or not. Results: The presented method has been tested on several test cases, both synthetic and real, and the results show that it is reliable and trustworthy, providing a consistent outcome with no user intervention even when dealing with complex defects. Conclusions: HyM3D method proved to be a valid alternative to the existing approaches for the digital reconstruction of a defective cranial vault; furthermore, with respect to the current alternatives, it demands less user interaction since the method is landmarks-independent and does not require any patch adaptation.

Keywords: Bioinformatics , Computed aided design , Cranioplasty , Statistical shape model , Surface Interpolation

An area of interest in orthopaedics is the development of efficient customized neck orthoses, considered that pathologies which affect the neck area are widespread. Advanced acquisition and modelling approaches combined with Additive Manufacturing (AM) can potentially provide customized orthoses with improved performance and complexity. However, in the design of these devices, besides functional and structural requirements, benefit and comfort of the patient should be a main concern, in particular, at the early stage of design during the acquisition of the body's part, and while using the printed orthosis. In this paper, a scanning system with three sensors was developed which allows a fast, about 5 s, and accurate acquisition of the neck area with minimum discomfort for the patient. A neck orthosis with a ventilation pattern obtained by Topology Optimization (TO), lightened by about 35%, was also established. In fact, a main role for comfort is played by the ventilation pattern which contributes both to lightness and breathability. Its structural and comfort performance was evaluated in comparison with an orthosis with a ventilation pattern configured by Voronoi cells. Structural assessment was carried out by means of finite element analysis under main loading conditions. An evaluation of neck temperatures in relation to wearing 3D printed prototypes, manufactured with Hemp Bio-Plastic® filament, was finally conducted by means of a thermal imaging camera. TO orthosis prototype showed a better performance regarding thermal comfort, with a maximum increase of neck temperature less than 1 °C, which makes the proposed configuration very promising for user's comfort.

Keywords: Additive manufacturing , CAD , Orthosis modelling , Reverse engineering , Thermal comfort , Topology optimization

Primary dentition is crucial in influencing the emergence of permanent teeth. Premature primary tooth loss can result in undesired tooth motions and space loss in the permanent dentition. Typically, fixed or removable dental appliances are adopted to maintain edentulous space until the eruption of permanent teeth. However, traditional space maintainers have limitations in terms of variability in tooth anatomy, potential allergic reactions in some individuals (i.e., nickel sensitivity), difficulties in maintaining oral hygiene, and patient acceptance. The present study introduces a fully digital framework for the design and manufacturing of customized pediatric unilateral space maintainers using generative algorithms. The proposed approach overcomes the current challenges by using a biocompatible resin material and optimizing the device's size, design, and color. The methodology involves intraoral scanning, surface selection, and trim, generative 3D modeling, finite element analysis (FEA), and additive manufacturing (AM) through vat photopolymerization. FEA results demonstrate the device's mechanical performance and reliability, while additive manufacturing ensures design freedom, high resolution, surface finishing, dimensional accuracy, and proper fit. The mechanical interlocking system facilitates easy and effective positioning of the device. This digital approach offers the potential for wider usage of space maintainers and can be further validated through experimental assessments and clinical studies.

Keywords: 3D printing , digital space maintainer , FEA analysis , generative design , pediatric dentistry

A way of presenting information in visual representations of technical systems influences the progress and the outcome of the engineering design process. Consequently, improving the means by and through which information is utilised during the process is one suggested approach to advancing engineering design. Engineers' interaction with visual representations of technical systems is mainly visual and virtual. Although such interactions are cognitively complex, little is known about cognition (mental information processing) underlying the utilisation of design information during engineering design. To narrow the research gap, this study explores how visual representations of technical systems affect engineers' brain activity while generating computer-aided design (CAD) models based on them. More precisely, the brain activity of 20 engineers is captured and analysed using electroencephalography (EEG) during the visuospatially-intensive design tasks of CAD modelling in two conditions; when technical systems are presented with orthographic and isometric projections in technical drawings. The results imply the sensitivity of engineers' brain activity in CAD modelling to the visual representation from which a technical system is interpreted. In particular, significant differences are found in theta, alpha, and beta task-related power (TRP) over the cortex when interpreting the technical drawings and CAD modelling from them. Furthermore, the results reveal significant differences in theta and alpha TRP when considering the individual electrodes, the cortical hemispheres, and the cortical areas. In particular, theta TRP over the right hemisphere and the frontal area seems essential in distinguishing neurocognitive responses to the orthographic and isometric projections. As such, the conducted exploratory study sets the foundations for exploring engineers' brain activity while performing visuospatially-intensive design tasks, whose segments are relatable to the aspects of visuospatial thinking. Future work will explore brain activity in other design activities that are highly visuospatial, with a larger sample size and an EEG device of a higher spatial resolution.

Keywords: brain , cognition , electroencephalography , engineering , physiology

As an initial step towards a better understanding of cognitive load in computer-aided design (CAD), the herein presented study investigated cognitive load imposed on 24 mechanical engineers during two CAD modelling tasks of intentionally different complexity levels. The cognitive load has been rarely studied in the CAD context, which resulted in the lack of understanding if and how the EEG-based indicators available from the literature reflect the changes in cognitive load imposed on engineering designers in CAD activities. Therefore, cognitive load was measured and analysed using three EEG-based indicators to explore insights that might be obtained from them. The initial analysis revealed different cognitive load results from the employed indicators for the same EEG data. In addition, the study implies that the cognitive load results obtained through the used indicators are only partially coherent with the CAD modelling task complexity. Hence, the results imply that the chosen EEG-based indicator matters when measuring and analysing cognitive load in CAD modelling tasks and that its adjustment for CAD context might be needed.

Keywords: Cognitive load , Complexity , Computer Aided Design (CAD) , Design cognition , Electroencephalography

This paper explores the suitability of Artificial Neural Networks (ANNs) as an enabler of Design Automation in the turbomachinery industry. Specifically, the paper provides 1) a preliminary estimation of the effectiveness of ANNs to define values for design variables of reciprocating compressors (RC) and 2) a comparison of ANNs performance with traditional and more computationally demanding methods like CFD. A tailored ANN trained on a dataset composed by 350+ Baker Hughes' RC automatically assigns values to 8 geometrical variables belonging to multiple parts of the RC in order to satisfy two target conditions linked to their thermodynamic performance. The results highlight that the ANN-assigned parameters return an optimal solution for RC also when the target values do not belong to the training dataset. Their predictive capacity for RC thermodynamic performance, with respect to CFD, are comparable (i.e. less than 2% in terms of calculated absorbed power) and the approach enables a significant gain in terms of computational time (i.e. 2 minutes vs 10 hours). Future perspectives of this work may involve the integration of this tool in an advanced DA method to lead Design Engineers (DEs) during the whole design process.

Keywords: Artificial intelligence , Computational design methods , Embodiment design , Optimisation , Turbomachinery

A fundamental outcome of bone tissue engineering is the regeneration of bone defects presenting large dimensions. A promising solution in biomedical practice is the implantation of biomimetic scaffolds, i.e. porous structures mimicking the natural shapes of healthy bone tissues, which are colonized by mesenchymal stem cells and that support the growth of the regenerating tissues, until the complete healing process is realized. This work presented a workflow for the geometrical modeling and the mechanical design of beam-based, bilayered, and conformal scaffolds, mimicking the human cortico-cancellous bone structure for filling a large dimension defect in the mandibular bone of an injured patient. An isotropic Voronoi topology built on a refined point set generated by a high-quality meshing algorithm was adopted for lattice generation, which led to an open-cell architecture characterized by full connectivity and uniform cell size. Such geometrical and structural features represent crucially important requirements for maximizing the osteointegration and the vascularization of the implanted scaffold. An irregular scaffold was modelled, including a cortical and a sponge layer. The beam radii of both layers were determined by matching the elastic properties of the corresponding bone tissues, thus minimizing the stress shielding effects. Interestingly, several scaffold properties deriving from the proposed procedure, such as the porosity and the pore size, were in good agreement with those reported in the literature.

Keywords: Biomimetic scaffolds , Bone tissue engineering , CAD modeling , Lattice structures , Mechanical simulation

Manufacturing process (MP) selection systems require a large amount of labelled data, typically not provided as design outputs. This issue is made more severe with the continuous development of Additive Manufacturing systems, which can be increasingly used to substitute traditional manufacturing technologies. The objective of this paper is to investigate the application of image processing for classifying MPs in an unsupervised approach. To this scope, k-means and hierarchical clustering algorithms are applied to an unlabelled image dataset. The input dataset is constructed from freely accessible web databases and consists of twenty randomly selected CAD models and corresponding images of machine elements: 35% additively manufactured parts and 65% manufactured with traditional manufacturing technologies. The input images are pre-processed to have the same colour and size. The k-means and hierarchical clustering algorithms reported 65% and 60% accuracy, respectively. The algorithms show comparable performance, however, the k-means algorithm failed to predict the correct subdivisions. The research shows promising potential for MP classification and image processing applications.

Keywords: Additive Manufacturing , Computer Aided Design (CAD) , Image Processing , Machine learning , Unsupervised Learning

Purpose: Left atrial appendage occlusion (LAAO) is a structural interventional cardiology procedure that offers several possibilities for the application of additive manufacturing technologies. The literature shows a growing interest in the use of 3D-printed models for LAAO procedure planning and occlusion device choice. This study aims to describe a full workflow to create a 3D-printed LAA model for LAAO procedure planning. Design/methodology/approach: The workflow starts with the patient's computed tomography diagnostic image selection. Segmentation in a commercial software provides initial geometrical models in standard tessellation language (STL) format that are then preprocessed for print in dedicated software. Models are printed using a commercial stereolithography machine and postprocessing is performed. Findings: Models produced with the described workflow have been used at the Careggi Hospital of Florence as LAAO auxiliary planning tool in 10 cases of interest, demonstrating a good correlation with state-of-the-art software for device selection and improving the surgeon's understanding of patient anatomy and device positioning. Originality/value: 3D-printed models for the LAAO planning are already described in the literature. The novelty of the article lies in the detailed description of a robust workflow for the creation of these models. The robustness of the method is demonstrated by the coherent results obtained for the 10 different cases studied.

Keywords: 3D Printing , Additive manufacturing , Heart model , Left atrial appendage occlusion , Left atrium , Stereolithography , Structural heart surgery , Surgical planning

Purpose: Timing constraints affect the manufacturing of traditional large-scale components through the material extrusion technique. Thus, researchers are exploring using many independent and collaborative heads that may work on the same part simultaneously while still producing an appealing final product. The purpose of this paper is to propose a simple and repeatable approach for toolpath planning for gantry-based n independent extrusion heads with effective collision avoidance management. Design/methodology/approach: This research presents an original toolpath planner based on existing slicing software and the traditional structure of G-code files. While the computationally demanding component subdivision task is assigned to computer-aided design and slicing software to build a standard G-code, the proposed algorithm scans the conventional toolpath data file, quickly isolates the instructions of a single extruder and inserts brief pauses between the instructions if the non-priority extruder conflicts with the priority one. Findings: The methodology is validated on two real-life industrial large-scale components using architectures with two and four extruders. The case studies demonstrate the method\'s effectiveness, reducing printing time considerably without affecting the part quality. A static priority strategy is implemented, where one extruder gets priority over the other using a cascade process. The results of this paper demonstrate that different priority strategies reflect on the printing efficiency by a factor equal to the number of extrusion heads. Originality/value: To the best of the authors' knowledge, this is the first study to produce an original methodology to efficiently plan the extrusion heads\' trajectories for a collaborative material extrusion architecture.

Keywords: Additive manufacturing , Collaborative manufacturing , FDM , MEX , Multiple heads , Toolpath planning

Modern industries are experiencing radical changes due to the introduction of high technological innovations. In this context, even more highly complex and customized products are required, increasing the need of tending towards the concept of complexity for free. In addition, new products are conceived with the circular economy in mind, considering possible multi life-cycle at the early design stage to reduce time and costs while ensuring high quality standards. To evaluate the overall product complexity, this research combines geometrical, manufacturing, assembly, and disassembly complexity features, typically treated separately in the literature. The research is divided into two parts and proposes a novel methodological framework for assessing product complexity with an overall view, integrating many aspects of product life cycle. The framework aims to create a rank of product configurations, on the base of complexity. Making complexity assessment procedures objective is essential to effectively support decision-making processes, especially when introducing advanced manufacturing technologies such as Additive Manufacturing (AM). Additionally, it is necessary to know the complexity of the individual components before the overall assembly. This paper deals with the first part of the research, proposing the aforementioned novel methodological framework, with a great focus on geometrical complexity. A geometrical complexity index is defined through experimental and numerical surveys, involving CAD modeling experts and considering numerous metrics found in the technical literature. The proposed methodological framework and the geometrical complexity metric can provide useful tools for businesses looking to evaluate their product complexity and identify areas for improvement.

Keywords: CAD , Geometrical complexity , Methodological framework , Product complexity , Survey

The fracture resistance of multilayer zirconia crowns has recently been proven to be improved by using lithium millable disilicate glass–ceramic blocks (D'Addazio in Materials, 2020). Accordingly, the framework and the ceramic coating are designed and milled using a CAD-CAM technology and the two separated prosthetic components are then manually assembled by the dental technician and glued with the fusion of a glass–ceramic material. It is essential, during the CAD phase, to design a gap between the framework and the decorative veneer that will later be filled by the fused ceramic.Since the act of gluing the two parts is manually performed by the dental technician, we aim at investigating the operator influence on the final gap with respect to the designed gap. For this purpose, an original geometrical investigation method was developed to enable the 3D digital analysis of the whole fusion interface. During the CAD design stage, two technicians input a different setting for the gap between the two components. The framework and veneering structure were designed, the milled components were produced, and the zirconia framework was sintered, then the two CAD-on prosthetic components were scanned before and after their fusion/crystallization to analyze the physical internal gap. The results show that manual assembly cancels out any effect of the precision settings adopted during CAD-CAM design of the components, as well as any benefit expected from machining on a CNC milling machine, thus requiring, as a last step, manually retouching the prosthesis to correctly fit in the mouth.

Keywords: Bioengineering , CAD modeling , Dentistry , Interactive design , Reverse engineering