Geometric modeling and processing

In the context of designing of customized products, ensuring the verification of requirements and stakeholder needs in an efficient and cost-effective manner poses significant challenges. This paper proposes a Virtual Prototyping approach, integrating Computer-Aided Design and multibody modelling, to leverage their respective advantages. The presented case study involves the integration of two pre-existing robots, a cobot and an Autonomous Mobile Robot, to realize an Autonomous Mobile Cobot tailored to the specific needs of a manufacturing industry. Through Virtual Prototyping approach, part of the requirements, including spatial and assembly constraint, are verified by means of CAD, while interaction and behavioural requirements are verified through multibody modelling and simulation. This work highlights the efficacy of Virtual Prototyping in achieving comprehensive design verification for tailored products. By simulating the behaviour and performance of the designed system before physical implementation, Virtual Prototyping reduces the time and costs associated with traditional trial-and-error methods. Moreover, it enables a more thorough exploration of design alternatives and optimization strategies, ultimately improving the efficiency and effectiveness of the design process.

Keywords: CAD , human-robot collaboration , multibody modelling , Virtual Prototyping

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

Lung sequestration is a rare congenital anomaly characterized by an abnormal mass of lung tissue. It can occur in two forms, either intralobar, where the mass is embedded within the lung tissue, or extralobar, where it develops outside the lung's boundaries. In both cases, removal of this defect involves a complex minimally invasive procedure during which, in brief, the sequestration is isolated and removed. The surgical removal of the pulmonary sequestration represents a complex challenge for surgeons who have to deal with many critical aspects, such as the heartbeat-induced movement of the lung and, in pediatric cases, very limited operating space. For this reason, it is crucial to create a realistic training program that faithfully reproduces the operating conditions and enables surgeons to become familiar with this procedure. The simulator proposed in this work offers a higher level of anatomical realism than existing systems, including critical details such as the visceral pleura and accurately reproduce spatial relationships between anatomical structures. Moreover, the simulation of cardiac motion adds an element of complexity that simulate the challenges of surgery. The simulator was tested in a realistic operating room setup, validating its practical applicability.

Keywords: CAD modeling , Cardiac motion simulation , Minimally invasive thoracic surgery , Pediatric surgical simulator , Pulmonary sequestration

Origami, a traditional Japanese art, has influenced engineering and shape memory materials design, enabling complex structures from simple folds. Fused filament fabrication (FFF) using polylactic acid (PLA) presents new landscapes for shape-changing structures. PLA, with its relatively low glass transition temperature (i.e. 55–65 ℃), exhibits an activable shape changing behavior within easily accessible temperature ranges and, even not at the human body temperature, can be a valuable and available material to demonstrate the intent mechanism. In this paper we investigate how PLA's shape memory properties together with tool path extrusion strategies can be harnessed within the framework of origami-inspired structures. The waterbomb origami structure has been implemented to analyze folding and shape memory mechanism. The influence of 3 different activation temperatures of the mechanism as well as 3 different printing toolpaths were evaluated on a single cell. Five elements were arranged on a cylindrical shape to ideally achieve a portion of a tracheal stent with a small diameter during the insertion phase, which increases when in place. The results obtained demonstrate the potential of combining techniques used in origami and shape memory materials for reducing the initial volume of a part, which can be useful in many applications, such as stents in the biomedical field. By identifying a suitable material, the stent can be reduced in size, minimizing the invasiveness of the surgical procedure.

Keywords: 4D printing , biomedical application , CAD design , origami , Shape memory polymer

Lattice structures are defined by the organised repetition of a unit cell. These complex designs are widely used in engineering due to their lightweight nature and tailored mechanical properties. This study presents a novel 1D numerical method for modelling the standard Body-Centered Cubic (BCC) unit cell, a commonly used lattice structure geometry due to its geometry simplicity. Mechanical analyses were carried out using Ansys 2023 R2. A customised ANSYS Parametric Design Language (APDL) routine was developed to assign specific area and inertia properties to each beam element, independent from the nominal value of the strut diameter. The equivalent engineering constants were evaluated through uniaxial compression and in-plane shear tests. A neural network optimisation technique was then employed to optimise the 1D model's parameters and improve its accuracy. The neural network was trained using high-fidelity 3D FEM results as the reference data, enabling the identification of the most suitable parametric values for various strut diameters. The proposed 1D method aims to address the computational complexity associated with traditional 3D FEM analyses while maintaining accurate predictions of the mechanical response. By representing the lattice struts as beam elements in the 1D model, the computational cost can be significantly reduced, making it more feasible to analyse large-scale lattice structures or perform extensive parametric studies involving different design configurations and loading scenarios. This formulation has been tested by comparing numerical results coming from standard 3D and 1D elements on a variable span 3-point bending test.

Keywords: FEM , Lattice Structures , Neural Network

Designing individualized orthodontic treatments for malocclusions and misaligned teeth is a complex task due to the numerous conditions that must be met. These conditions include personal patient considerations, technical constraints, physiological restrictions, and specific instructions from orthodontists. Achieving the ideal final dental arrangement remains a significant challenge in orthodontic practice. The current process primarily involves collaboration between orthodontists and technicians, using manual procedures and specialized software. This study describes the formalization of a model designed to simplify this orthodontic procedure. The creation of a patient's final dental configuration, necessary for manufacturing all the devices for the treatment plan, is automated using a mathematical model based on current knowledge in the field. The mathematical model has been incorporated into a modeling and animation software tool, and a case study has been tested with a manufacturer specializing in orthodontic devices. The comments received highlights the usefulness of the proposed algorithm and its value as a significant resource for discussing with orthodontists.

Keywords: Design method , Knowledge formalization , Orthodontic treatment , Product customization

This article investigates the cognitive load (CL) in the underexplored context of computer-Aided design (CAD), focusing on identifying the most effective electroencephalography (EEG) features for measuring CL variations. While previous research has demonstrated that the EEG can distinguish between CL levels in various domains, there is limited understanding of whether existing EEG-based indicators can accurately reflect CL changes in CAD activities. To address this gap, the study first extracted a list of potential EEG-based CL indicators from the literature and then evaluated their applicability to CAD tasks through an experimental study involving 24 engineering designers performing CAD modeling tasks of varying complexity. The experimental study employed two complementary methods: NASA TLX as a subjective measurement and EEG as a psychophysiological measurement, enabling a comprehensive analysis of the CL in CAD tasks by validating and comparing the findings from both methods. The results revealed six EEG features sensitive to changes in the CL, with an increase in parietal alpha task-related power emerging as the most prominent indicator. This study makes a novel contribution by examining the relationship between the EEG-based CL indicators and the NASA TLX scores, highlighting meaningful correlations, and emphasizing the importance of both frequency bands and cortical areas when interpreting EEG signals in relation to CL. © 2025 American Society of Mechanical Engineers (ASME).

Keywords: cognitive ergonomics , cognitive load , computer-aided design , electroencephalography , human performance

The engineering-to-order (ETO) sector, driven by the demands of new energy transition markets, is witnessing rapid innovation, especially in the design of complex systems of turbomachinery components. ETO involves tailoring products to meet specific customer requirements, often posing coordination challenges in integrating engineering and production. Meeting customer demands for short lead times without imposing high price premiums is a key industry challenge. This article explores the application of artificial neural networks as an enabler for design automation to deliver a first tentative optimal design solution in a short period of time with respect to more computationally demanding optimization methods. The research, conducted in collaboration with an energy company operating in the Oil & Gas and energy transition markets, focuses on the design process of reciprocating compressors as a means of study to develop and validate the developed methodology. Three case studies corresponding to as many representative jobs related to reciprocating compressor cylinders have been analyzed. The results indicate that the proposed method performs well within its training boundaries, delivering optimal solutions and providing reasonably accurate predictions for target configurations beyond these boundaries. However, in cases requiring a creative redesign using artificial neural networks may lead to errors that exceed acceptable tolerance levels. In any case, this methodology can significantly assist design engineers in the efficient design of complex systems of components, resulting in reduced operating and lead times. © The Author(s), 2025.

Keywords: design automation , engineering design , machine learning , neural networks , product development

Lattice Spring Models (LSMs) are fast and stable simulation methods based on networks of discrete deformable elements, well-suited for large deformations or topological changes in real-time applications. Considering that the identification of spring network topologies and elastic constants lacks standardization, defining a robust design workflow for LSMs would promote their wider adoption, enabling efficient and green simulations. In this work, the essential requirements to obtain optimal spring distributions for physically consistent LSM were outlined. Intrinsic rigidity, homogeneity, isotropy, and boundary conformity were identified as fundamental conditions for achieving realistic behaviors of deformable lattices. To generate optimal spring networks, the possibilities offered by high-quality unstructured triangular and tetrahedral meshes were explored, since they satisfy all the outlined design requirements. Several topological metrics were defined and applied to clusters of spring network samples, with the aim of comparing different lattice topologies. By discussing the obtained results, a series of useful considerations were pointed out, and many best practices to generate optimal mesh-derived lattice configurations were clearly identified. The optimal LSMs were validated on several case studies, including comparisons to dual FEM models, analyses on anisotropic spring networks, and fracture simulations, thus giving highly encouraging results.

Keywords: Lattice spring model , Modeling , Simulation , Tessellation , Topology metrics , Triangular and tetrahedral mesh

This paper presents a novel workflow for designing and fabricating patient-specific cranial implants and surgical guides using advanced CAD and 3D printing technologies. Developed at the T3Ddy Lab at Meyer Children's Hospital, the methodology includes close collaboration between engineers and neurosurgeons, allowing for rapid prototyping and real-time adjustments. The workflow involves designing a cutting guide for precise bone resection and a custom cranial implant for anatomical reconstruction, both using titanium alloy for its biocompatibility and mechanical strength. The setup enhances efficiency, ensuring precise device fit and improving surgical outcomes. The paper presents the general framework established to design custom made medical devices for skull repairing surgery. The CAD modeling phase of the surgical guide and cranial implant are described in detail, highlighting developed solutions to improve the effectiveness of the technology. The proposed workflow was validated in multiple clinical cases, demonstrating improved surgical precision, reduced operative time, and enhanced recovery.

Keywords: 3D Printing , CAD , Cranial Implant , Cranioplasty , Craniotomy , Surgical Guide

A major challenge in constructing models of the human body or body parts stems from the fact that they are actually composed of several solid bodies articulated together. Consequently, 3D models must be parameterised with reference to joint angles: scans of the foot taken at different plantar/dorsal flexion angles were used in this study as a benchmark. The imple-mented methodology was based on the regression fitting of landmark trajectories obtained on a limited number of foot poses; these same landmarks were then used to guide 3D mesh morphing to predict foot geometry at different plantar/dorsal flexion angles. A careful optimi-sation of the methodology was performed to identify the optimal set of foot scans. The comparison between the actual foot shapes obtained by 3D laser scanning and the predicted shapes showed that the average error is at most 6.57 ± 2.74 mm. The methodology indications were finally drawn based on these error estimates. Further works will consider combined motions including flexion/extension, internal/external rotation, and foot inversion/eversion. © 2025 by the authors of this article.

Keywords: 3D laser scanner , 4D model , foot landmarks , mesh morphing , shape prediction

Intraosseous access is a critical emergency procedure for introducing fluids and blood components into the systemic circulation, necessitating thorough training for healthcare personnel. In collaboration with Meyer Children's University Hospital IRCCS, the Department of Industrial Engineering at the University of Florence has developed a high-fidelity, low-cost pediatric simulator specifically for intraosseous access in the proximal tibia. Using Materialise Mimics 26® software, anonymized tomographic images of a 5-year-old patient were processed to obtain the three-dimensional geometry of relevant anatomical structures: tibia, fibula, distal femur, muscles, and skin. These models were further refined with Geomagic DesignX® for the final simulator design. The simulator features silicone replicas for soft tissues, with rigid structures and silicone casting molds produced through Fused Deposition Modeling. Preliminary tests were conducted to select suitable materials, which were then evaluated by specialized medical personnel using the EZ-IO® device to ensure accurate haptic feedback. The resulting simulator provides a realistic platform for intraosseous access training, enabling healthcare practitioners to enhance their procedural skills and ensure patient safety.

Keywords: additive manufacturing , intraosseous access , pediatric mannequin

This paper presents a scalable, open-source method for designing strut-and-node lattice structures for industrial applications, including uniform and graded lattices. Traditional computer-aided design tools struggle with lattice structures with high complexity, prompting the need for alternative approaches. While function representation techniques are commonly applied to triply periodic minimal surface lattices, their use for strut-and-node lattices has been limited. The proposed method defines the unit cell geometry using function representation primitives to model cylindrical struts and spheres, followed by isosurface triangulation and spatial replication within a voxelized design space. To showcase its practical application, two case studies are presented in which industrial components are filled with uniform and graded lattice structures using the newly developed model. The paper includes a comprehensive analysis of the computational cost of the approach. Furthermore, the study evaluates the geometric accuracy and quality of the generated lattice, highlighting their suitability for lightweight design in additive manufacturing. This method eliminates the need for boundary representations of lattice structure models, leading to more efficient data handling. The results of this research have broad implications for developing 3D components optimised for additive manufacturing. The approach targets industrial use, enabling fast, efficient design of complex, lightweight geometries. © 2025 The Author(s).

Keywords: additive manufacturing , CAD file format , computer-aided design , Lattice structures , lightweight design

Nature-inspired metaheuristics have proven effective for addressing complex structural optimization challenges where traditional deterministic or gradient-based methods often fall short. This study investigates the feasibility and benefits of embedding three prominent metaheuristic algorithms, the Genetic Algorithm (GA), the Firefly Algorithm (FA), and the Group Search Optimizer (GSO) embedded into the ANSYS Parametric Design Language (APDL). The performance of each optimizer was assessed in three case studies. The first two are spatial truss structures, one comprising 22 bars and the other 25 bars, commonly used in structural optimization research. The third is a planar 15-bar truss in which member sizing and internal topology were simultaneously refined using a Discrete Topology (DT) variable method. For both the FA and the GSO, enhanced ranger-movement strategies were implemented to improve exploration–exploitation balance. Comparative analyses were conducted to assess convergence behavior, solution quality, and computational efficiency across the different metaheuristics. The results underscore the practical advantages of a fully integrated APDL approach, highlighting improvements in execution speed, workflow automation, and overall robustness.

Keywords: ANSYS APDL , finite element analysis , firefly algorithm , genetic algorithm , group search optimizer , nature-inspired metaheuristics , optimization

The Reynolds-averaged Navier-Stokes (RANS) equations are the industry-standard computational fluid dynamics method for estimating forces, viscous effects, and boundary layer behaviour in various flow conditions, including adverse pressure gradients and flow-separation regimes. However, despite the ever-increasing availability of computational power, there are several scenarios in which more rapid methods, based on suitable simplified assumptions, offer advantages with respect to the RANS approach. Foil devices often operate at low angles of attack, high Reynolds numbers, and without fluid separation. These conditions make the Vortex Lattice Method (VLM) a viable and faster alternative for exploring the wide design space of yacht foils. In this study, the hydrodynamic forces generated by various foil geometries are computed using an original VLM formulation for generally curved lifting surfaces. The case study is focused on the foils of an ecofriendly dinghy designed and manufactured by students in the international framework of 1001VELAcup.

Keywords: CAD modelling , Computation fluid dynamics , Foil design , Vortex lattice method

The quantitative assessment of the degree of order in a set of points is the subject of extensive investigation in discrete geometry. In this context, the Voronoi diagram finds applications across various fields, including medicine, biology, logistics, theoretical physics, and engineering. In the engineering domain, particularly in product design, the exploration of spatial order generates interest in the study and design of lattice structures or topological optimization. These specific applications contribute to enhancing certain characteristics of a structure or component, such as ergonomics, the quantity of material used, and mechanical properties. Delaunay triangulation, the dual of the Voronoi diagram, stands out as one of the most widely used algorithms for generating triangular meshes from point clouds. This work explores the analysis of primary entropic methods employed to evaluate the degree of order in Voronoi tessellation and Delaunay mesh. It Introduces an innovative approach centered on calculating the differential entropy of Voronoi seeds, which correspond to the vertices of Delaunay triangulation. The study shows the potential of the obtained results, both in terms of global and semi-local evaluations of the Delaunay mesh. It identifies novel usage scenarios within the context of product design. The results are thoroughly discussed and compared with other commonly utilized methodologies.

Keywords: Delaunay triangulation , Differential entropy , Mesh quality , Point clouds , Voronoi tessellation

In the project development of large fusion machines, the alignment and assembly phases represent an open challenge. Each mechanical component that constitutes the whole machine assembly and fixtures is affected by an intrinsic geometrical variation due to manufacturing and assembly processes. The complexity of the assembly together with the unavoidable geometrical imperfection can affect the expected machine functionalities. In this context, Reverse Engineering activities, aiming at obtaining the as-built of the components, coupled with virtual fitting studies, defining optimum alignment using the real shape of the components, become powerful risk mitigation tools in the assembly phases. This work presents a systematic method, complementary to the methodology currently followed in the ITER project, for the as-built management and for the validation of alignment phases of such a complex assembly. The first phase is to identify the key assembly requirements which drive the alignment of the ITER assembly. Then, the database for the requirement collection is clearly organized following the proper nomenclature rules and its architecture for data collection and analysis is indeed set up.

Keywords: Alignment , As-built Management , Assembly Requirements , ITER tokamak , Requirement Management , Virtual Fitting

Hygienic design concerns the need for making food processing machines and plants compliant with a series of specific requirements aimed at preventing bacteria contamination of food products. The sources available in literature for hygienic design guidelines are mainly represented by guidelines provided by specific organizations (e.g.: EHEDG in Europe and 3A Sanitary Standards in US), but a structured database and an engineering tool allowing for a quick reference by the designer is still missing. The aim of this paper is to illustrate the preliminary work aimed at developing a CAD-based tool able to analyze CAD models of machines and plants and to automatically recognize those features which break some hygienic design rules, allowing therefore the possibility to detect and fix them in an early stage of the design process. This work started from the collection of several guidelines, considering both the literature sources and also the hygienic design knowledge developed within companies. The acquired knowledge is then stored into a database and structured consistently with a specific syntax according to a selected ontology. A case study with two practical examples is exploited to validate the method. Results show the usefulness of the approach to avoid the need for several design reviews and the benefit that a tool implementing this knowledge-based system could bring to the designer.

Keywords: Design for manufacturing , Food equipment , Food industries , Hygienic design , Knowledge-based system

The advent of virtual simulation and Augmented Reality has had a profound impact on industrial processes, enhancing operational efficiency and optimising production workflows. This paper presents a comprehensive study on the development and implementation of a Mixed Reality Lab designed for the assembly and disassembly of industrial products. The primary objective is to create an advanced and intuitive Virtual Reality (VR) environment that facilitates industrial operators' learning and reduces training time while minimising errors. The project encompasses the scanning and 3D modelling of industrial components using various technologies, including photogrammetry, structured light, laser scanning, and LiDAR. These techniques are evaluated for their precision and effectiveness in generating accurate 3D models. The VR environment is developed using Unity, incorporating features that support interactive and immersive user experiences. Detailed methodologies for the creation and refinement of point clouds, mesh generation, and virtual environment setup are provided. The assembly and disassembly processes are tested using a brake assembly as a case study, thereby demonstrating the system's ability to manage complex industrial tasks. The results indicate significant improvements in training efficiency and operational precision, with potential applications across various industrial sectors.

Keywords: Mixed reality , Simulation , Training , User-centred application

In recent years, maritime industries have focused their attention on hydrofoils as one of the main technologies for the development of eco-sustainable solutions in the field of boating. The aim of the current research was to analyze the front wing of a Kohlkida class hydrofoil and to describe the methodology employed for the reconstruction of the 2-D airfoils by means of photogrammetry. Considering the limitations of the photogrammetry methods, some sections were extracted from the model. The airfoils were properly scaled and first compared with the model obtained by means of a laser scanner. Under the operating condition of the hydrofoil and with the use of Reynolds-averaged Navier–Stokes simulations, the behavior of the airfoils was simulated, allowing us to verify how the geometric differences due to the photogrammetry approach affect the fluid dynamics, in comparison to the model obtained from laser scanning. The proposed methodology led to a geometry reconstruction with adequate accuracy for the identification of both the characteristic curves for the lift and drag coefficients with a maximum error of 6% in the angle-of-attack range investigated in the study, also highlighting fluid dynamics problems that characterize this type of airfoils with a flat bottom and a knife-sharp leading edge.

Keywords: Computational fluid dynamics (CFD) , hydrofoil design and modeling , laser scanning , measurements , photogrammetry , reverse engineering