Design Tools and Methods in Industrial Engineering III

This work is aimed to set-up a methodology for foot shape prediction at different flexion angles, overcoming limitations encountered when different poses are required but a limited set of acquisitions can be performed. The basic idea was to identify a fitting law able to interpolate positions of foot anatomical landmarks, and then use this information to guide the deformation of an average foot shape. First of all, mesh correspondence between foot geometries was accomplished by an established procedure based on mesh morphing. Then Procrustes analysis was applied to the dataset to remove rigid motions and estimate the average shape. Two interpolation laws (linear and quadratic) were investigated and the best one in terms of prediction of 3D landmarks’ coordinates was identified. Finally, shape geometries at any flexion angle were predicted performing a second mesh morphing guided by interpolated landmarks’ displacements from the average shape. These analyses proved that a limited number of interpolation angles provides a prediction accuracy comparable to that obtained using all the angles available in the dataset. Moreover, predicted shapes have been compared to the actual scans in terms of root mean square error between corresponding nodes, obtaining a mean value of 4.03 ± 1.39 mm, in accordance with data reported in literature.

Obstructive Sleep Apnea (OSA) is a nocturnal respiratory disorder characterised by recurrent episodes of partial or total obstruction of the upper airways due to the collapse of the pharyngeal tissue. Mandibular Advancement Devices (MADs) restore regular breathing during sleep by advancing the lower jaw in a controlled way to increase the upper airway volume. However, the relaxation of muscle tone that naturally occurs during sleep induces a vertical mouth opening that impairs the efficacy of the treatment. Thus, elastic bands are recommended to keep the mouth firmly closed. Despite successfully treating OSA, inadequate evidence exists about the effects of MADs supported by elastic bands on teeth and Periodontal Ligaments (PDLs).This study aims to develop a numerical simulation approach through the finite element method to evaluate the behaviour and the effects (displacement and stress fields) of MADs embedded with intermaxillary elastics on PDLs and teeth of patients suffering from OSA. Findings confirm the efficacy of elastics in controlling the mouth opening and reveal a stress increase at the anchorage regions. Thus, their use should be advised to patients who do not suffer from periodontal problems in the anterior region of the mouth.

Current technological developments in the field of sensor capture and additive manufacturing (AM) from computer models have led to innovative solutions for a 3D reconstruction of anatomical parts of the human body in real time, enabling interesting applications in the medical field and especially in orthopedics. The following work proposes the use of new technologies applied to tele-rehabilitation so that the patient can benefit from remote rehabilitation services. The wrist motion performed by the physical therapist was to be compared with the wrist motion of the patient undergoing rehabilitation, so as to obtain a proper analysis on the treatment to be followed, the expected timing and the recovery goals. Future applications could involve the use of the proposed system within hospitals and rehabilitation centers in order to support health care providers, improve patient care and quality of life, and contribute to the innovation of new approaches for medical assessment.

The paper proposes a new recognition rule to automatically identify the spine line by detecting vertebral apophyses from discrete models of human backs collected by 3D scanning. Unlike previous 3D optical approaches, the process described here aims to directly detect spinal apophyses, following the posturologist’s method. These anatomical landmarks are identified not as areas of the back surface with specific shapes, but by searching for appropriate local shape perturbations. Except for vertebral prominences that are convex regions, spinal apophyses are generally unrelated to specific surface shapes. The rule has been tested on several human backs. For each, an experienced operator identified the spinal apophyses from palpation and indicated their position by applying an adhesive marker on the back surface. These positions are used as a reference to compare the vertebral apophyses automatically localized by the methodology proposed here. The experimental results show that the rule discriminates well even blurred vertebral prominences.

The work here presented elaborates an analysis of the retinal images, with the aim of characterizing their morphological conformation through the recognition of remarkable parameters such as, among all, the number of vessels, terminal points and bifurcation. The correct identification of each single vessel belonging to the vascular distribution represents a point that has not yet been fully consolidated by the scientific community. The reason lies in the fact that the interpretation of enface images, in which the distribution of the vases is imprinted on a two-dimensional plane, makes it difficult to discern each single section of the vase by following its entire spatial development, due to the multiple overlaps with different pot portions. The aim of this research work is to ensure that the limits encountered in modern retinal image processing algorithms are overcome, through the use of an evaluative comparison of contiguous vessel portions on the basis of local dimensional and intensity similarity criteria. In this way, it is possible to trace the correct attribution of the spatial placement of each vessel, taking it into account in the relative classification in the entire vascular branch of clinical interest.

The present research work intends to examine the anatomical distribution of cerebral vessels, starting from the automatic processing of diagnostic image acquisition sequences, with the aim of identifying the characteristic parameters of their structural conformation, such as terminal points and bifurcations, and statistic connotations closely associated with the formation of pathological phenomena. To do this, a local connectivity investigation was used which, starting from the reconstruction of the central axis crossing the vessels, elaborates a process of sequential ordering of each section with the aim of investigating the spatial conformation of the vessels structure, identifying branches and regions of origin. The proposed algorithm also elaborates a punctual analysis of the vascular branches, giving rise to a three-dimensional reconstruction of the morphological and topological characterization of the vessels in support of the clinical examination. The aim is to provide a fast and accurate procedure capable of automatically interpreting diagnostic analyses of brain vessels to support clinical investigation.

Nowadays the interest for improving methodologies to design customized external devices for the neck has considerably grown, considered that neck pathologies are widespread among the population. Their design for additive manufacturing starts by acquiring the body’s part and, in order to achieve a satisfactory end result, the support of accurate reconstructed models from fast scans is relevant. At this aim, the availability of an average or statistical model could be potentially useful for reducing acquisition time and for upgrading low-resolution scans. This paper focuses on the application of a methodology for the creation of an average model of human neck. The method required the use of a set of scans, acquired by means of a structured light scanner, from which an accurate reconstruction of the neck surface was obtained. A number of healthy subjects of both genders was considered and the digital neck surfaces were used for creating an average digital model for males and for females. The methodology developed was based on mesh morphing and was applied to the sample considered with satisfactory results. The procedure is also suitable for the development of statistical models of the neck, that will cover future research.

Machine Learning (ML), part of Artificial Intelligence, is one of the enabling technologies of Industry 4.0. ML appears to be an effective, affordable, accurate and scalable technique to cost mechanical parts in the early stage of the design process. Despite the cost estimation methods proposed in the literature, their application in specific real industrial contexts (e.g., engineered-to-order products) is minimal.This paper presents an innovative method for developing ML-based parametric cost models. The training data set is generated thanks to an analytical and automatic software tool for cost estimation. The data is subsequently processed using the Cross Industry Standard Process for Data Mining – CRISP-DM method. CRISP-DM is a process model for data science and representation. It provides an overview of the data mining life cycle. Its flexibility and easy customisation allow the creation of a data mining model that fits the goal of this work.The proposed method was employed to develop two cost models (semi-finishing and finishing phases) for components (disks) of a gas turbine. Gradient Boosted Trees turned out to be the best-performing prediction algorithm. Design engineers successfully used the generated cost models while configuring the gas-turbine cross-section.

Batteries are becoming increasingly important due to their many applications in sectors such as energy, transport, and electronic devices, making them a key component for the green industrial revolution. Supranational bodies as the European Commission also recognize their importance. Batteries have critical issues throughout their life cycle that hinder a true ecological transition, including the use of critical raw materials, high carbon footprint in manufacturing processes, and difficulties in recycling and disassembly at end-of-life. To address these issues, eco-design is the only model capable of reducing or eliminating the problems at the root, improving the impacts of the upstream phases and the effectiveness of the downstream ones. The purpose of this study is to provide a dedicated theoretical framework for eco-design based on existing methodologies, which can be adapted to any scenario and considers all actors of the selected and involved value chain. This framework attempts to eliminate the issues and uncertainties of previous studies and enable the achievement of a truly optimized, feasible, and sustainable design.

Designers need to be aware early in the design phase of the environmental impact of their choices over the entire product life cycle. This paper proposes an eco-design method to support designers of different categories of electric vehicles, such as self-driving vehicles, cars, shuttles and buses. The methodology developed aims to realize a model for predicting the environmental impact of industrial electric vehicles. The proposed approach exploits machine learning methods to develop models with the design features of a generic electric vehicle, such as vehicle mass and distance traveled during its entire lifetime as independent parameters, to estimate the emissions of new products. The environmental impact indicator for this study is Climate Change, the dependent parameter chosen for the impact model. Machine learning algorithms were trained on training data retrieved from an automatic environmental impact estimation software tool based on an analytical approach. All stages of the product life cycle have been considered in the construction of the database, and the model provides quantitative results that consider the consumption of material and energy resources. Finally, the model is tested by estimating the environmental impact of a tourist shuttle.

Natural disasters have a significant effect in terms of impacted individuals and casualties. Artificial Intelligence (AI) techniques for automatically segmenting landslides from aerial photos is a relatively new field of research. Segmenting landslips quickly and accurately can significantly aid in assessing the damage caused by natural disasters. This research aims to compare the performance of AI techniques with more classical methods for the automatic segmentation of landslides from aerial images for damage assessment.It is presented a dataset of satellite images containing landslides collected in the Broni (Italy) region and annotated to train and test the segmentation model. Both classical image processing techniques, such as thresholding and edge detection, and AI-based methods, such as U-Net, are applied to the dataset.Overall, this research demonstrates that AI-based methods are a promising tool for automatically segmenting landslides from aerial images and can be a powerful asset in assessing the damage caused by natural disasters. The study also highlights the importance of combining classical and AI-based methods for better performance, especially in challenging and complex scenes.

The EU has established specific design requirements for Energy-related Products (i.e., EU 2017/1369). This study aims to compare the environmental impact of two different technologies used in electric kitchen hobs through Life Cycle Assessment (LCA). Specifically, a comparison between a radiant hob and an induction hob is provided with a cradle-to-grave perspective in various use scenarios (i.e., Italy, France, Sweden, and Germany). This comparison provides valuable insights into the identification of environmental hot spots of these products. After the LCA interpretation, eco-design solutions have been proposed for hobs development oriented towards improved life cycle performances.

A novel device based on non-Newtonian fluids for the attenuation of tangential impacts energy in helmets has been designed and tested. Non-newtonian shear-thickening fluids have provided the best energy attenuation in tangential impacts model tests. The system is made of a series of pads with a case containing the fluid in which is immersed a rigid pin, able to move in all direction. This movement permits to absorb tangential impact energy during its movement. A series of seven pads have been used to modify a motorcycle helmet made of two concentrical liners made of polystyrene. The liners have been only connected by pads and therefore are free to rotate. Oblique impacts tests on the helmet have shows a 14% reduction of the brain injury criterion. Moreover, the maximum of the rotational acceleration is moved to longer times, indicating a retard of the acceleration of the head due to the effect of the pads. The novel system can be applied with minimal modifications in most sport and motorbike helmets.

Auxetic foams and lattices are a promising class of materials characterized by a negative Poisson ratio which due to their outstanding properties (e.g. multi-impact behaviour and flexibility), can be used in designing next-generation sport equipment. We present an application of these materials in the sport field, suggesting a viable alternative to the current systems with enhanced comfort. Auxetic designs have been employed for the production of ergonomic shoulder straps for sports backpacks, to improve their overall comfort by exploiting the expansion of auxetic cells under tensile loads. Further optimization of the proposed application can be achieved in the future by using the collected data in analytical models to predict the behaviour of these systems.

Performance diagnostics, such as monitoring athletes’ movements, are essential for enhancing their performances. Wearable sensor networks are commonly employed for this purpose. However, designing such networks can be complex and often necessitates expensive and time-consuming pilot studies. To address this, we propose utilizing multibody models and digital sensors to simulate human movements and virtually test the development of sensor setups. In this study, we present an improved multibody model of the human upper limb, building upon an existing virtual environment from the literature for simulating human gestures. Our model incorporates a streamlined representation of the human torso and clavicle, along with their corresponding joints. The primary objective is to introduce a novel actuation method for the updated model, which only requires the positions of a predefined point as input, utilizing inverse kinematics to define the joint parameters. This approach reduces the amount of data required for simulation. To showcase the capabilities of this method, we acquired and utilized the trajectories of the center of gravity of the hand of a handball player executing a set shot to animate the multibody model. During the user study, the reference trajectories were compared to the trajectories obtained for the hand model during the simulation, revealing a strong agreement and affirming the feasibility of the proposed method.

The pressure exerted by trekking backpacks (BPs) of different volumes and construction designs was measured in six female users using a pneumatic sensor. The aim was to investigate the effects of gender-specific design on ergonomic comfort. Although no difference was found in terms of pressure in the female BP models, a correlation was found between pressure and biometric characteristics (BMI, chest and waist circumference). The results suggest that the ergonomic comfort of BP depends on the size of the user, with slim users more likely to experience uncomfortably high pressure from shoulder straps and hip belt.

The sport of bouldering is enjoying growing popularity worldwide, not least following its inclusion as an Olympic discipline in climbing. Impact protection mats are among the central pieces of equipment in climbing gyms. When new, these mat systems must have certain damping properties, which are determined in laboratory tests using a free-falling test weight.Experience has shown that the damping properties diminish through use in the climbing hall, so that after a few months to years, replacement by the hall operators is necessary. The aim a current project is to replace petroleum-based foamed plastics as the damping layer of climbing mats. In the first phase of the project, various mat systems available on the market were analyzed in detail and subjected to a standard test to determine the impact absorption capacity. It was shown, that several layups and designs fulfilled the performance criteria in terms of maximum deceleration, relative penetration depth, and coefficient of restitution.

Ice hockey has one of the highest concussion rates in sport. A step towards understanding and addressing limitations in current helmet technologies is widespread and accessible testing. A simplified test protocol to assess ice hockey helmet impact properties, especially during collision head impacts, has recently been introduced. The reduction of required laboratory equipment and the feasibility of modifications to standard test protocols are expected positive outcomes of this new method. No study has examined the repeatability and reproducibility for multiple appraisers, leaving uncertainty about the method’s feasibility for use in academic research or certification standards.A proportion of the original data collection (11 impact scenarios, 66 total impacts) was repeated by a second appraiser with no previous involvement or experience in developing or using the test method. A reliability analysis using intra-class correlation coefficients (ICC (2, k)) was conducted to supplement the intrarater reliability assessment previously performed. The ICC scores suggest good to excellent interrater reliability across linear and angular acceleration measurements, providing further evidence for the test methods reliability.

Ice hockey has one of the highest concussion rates in sports. A challenge in preventing concussions and developing helmets is the range of common head impacts. Currently, helmets provide increased protection during falls on the ice – what they are tested for in certification standards – but not during collisions between players that cause ~90% of concussions. Current helmet liners possess high stiffness to efficiently absorb impact energy during falls causing them to only partially compress during collisions. Hence, energy absorption is limited, leaving wearers susceptible to concussions. Reducing liner stiffness is not feasible, because protection during more severe impacts could be compromised. A helmet that can adapt its response to the occurring impact situation may enhance provided protection.A proof-of-concept study, to assess a mechanical metamaterial’s feasibility as an adaptive helmet liner, was undertaken. Compression tests of unit cells and cellular structures of the material at different strain rates (0.83, 8.3, and 83 s−1) suggest ~2.5-fold increased forces during compression and altered shapes of force vs. displacement traces. Such a switch in stiffness could facilitate helmet developments that maintain high protection levels during severe impacts while enhancing protection during impacts with more compliant bodies.

The prevalence of violence and blunt weaponry that Public Order (PO) officers are exposed to, place them at high risk of traumatic brain injury (TBI). Recreating these injurious occurrences, to assess protective equipment performance, can be problematic due to issues of repeatability when experimentally recreating PO threats. This led to the design of a bespoke helmet impact system. Following review of current test methods, the chosen design was a low-friction drop tower, compatible with anthropometric headforms as cradled, rigidly mounted, or affixed with a surrogate neck. Finite Element and torque calculations were used to optimise load bearing components, whilst maintaining low mass and safety requirements. The final system permits impact conditions in range for PO threat recreations, as well as meeting the standard test criteria of all non-vehicular sports, public sector and construction application standard drop tests.

This paper describes a robust design approach to optimize the design of smart shorts for muscle activity analysis. A practical application related to electromyographic shorts for monitoring six main thigh muscles is shown. Starting from a 2D digital model of a pattern block related to the shorts, a robust design approach is applied to optimize the design of textile electrodes for surface electromyography analysis in terms of size (i.e., diameter), and location (i.e., inter-electrode distance). The aim is to reduce the sensitiveness to noise factors (i.e., skin lubrication condition, anthropometric variability and gesture type) guaranteeing the best performance in terms of Signal Noise Ratio. The experimental campaign related to football activities allows the practical application of the proposed approach for the design of smart shorts for football. The results allow to define the optimal configurations for the six muscles of interest. This work might pave the way for the development of tailored smart garments for electromyography analysis.

Reduction of aerodynamic drag is a crucial aspect of cycling. Currently, to optimize aerodynamics, athletes rely on wind tunnel tests or CFD simulations. Despite the undeniable advantage of the latter in terms of cost and time effort, they still require validation through wind tunnel measurements. This paper introduces a novel workflow that aims to streamline and accelerate the aerodynamic analysis process for cycling. The proposed workflow focuses on utilizing a full-sized mannequin and integrates CFD simulations, wind tunnel validation, 3D scanning, and rigging animation techniques. The animation technique involves the creation of a virtual skeleton that allows the scanned model to be posed in any desired position, eliminating the need for physical adjustments and repetitive wind tunnel testing. To showcase the time-saving advantages of this approach, a steady CFD analysis is conducted to compare six different configurations obtained using the rigged model, in terms of drag areas, velocity streamlines, and pressure coefficient distribution. The obtained data trends closely align with previous similar studies in the literature and the results from the simulation have been compared with wind tunnel test measurements. Additionally, future adjustments to the position or equipment can be easily made using the virtual rigging model. By integrating virtual techniques with CFD simulations and wind tunnel validation, the proposed workflow enables rapid evaluation of aerodynamic performance in a more efficient and cost-effective manner.

This work discusses the development and application of a parametric CAD model of the human bronchial tree, for use in computational fluid dynamics simulations. The model, which represents the trachea, bronchi, and early airway bifurcations, is based on geometrical parameters derived from existing literature. It can be edited by easily varying parameters in an external spreadsheet, offering an efficient alternative to patient-specific models, which often require the use of time-consuming segmentation procedures. The developed model was utilized to run fluid dynamic simulations, including a scenario that represents respiratory system dysfunctions. These are typical of diseases such as acute respiratory distress syndrome, which can be also triggered by recently emerged COVID-19. The results of these simulations were critically analyzed: they turned out to be consistent with the stated objectives and methods, even in the context of the existing literature. The paper concludes by discussing the limitations and potential improvements of the research.

The engineering design phase usually requires the integration of different types of studies and analyses for the definition of the whole system. Depending on their nature, these studies can be carried out thanks to specific FEM models and tools which differ from each other on the basis of the physics problem under investigation. A proper methodology for integration of different analyses is needed, in order to transfer information and integrate the multi-physics issues. The aim of this paper is to present a methodological framework supporting the analyses integration process and the results assessment. Based on a CAD-centric approach, the framework is applied in the software Ansys Workbench, to show how to deal with this problem in such tool, thanks to the Import Load function. A study case is considered in the nuclear fusion research field: multiphysics analysis on DEMO divertor, where several physics interact with each other due to the relevant complexity of such systems. In this study, force results from FEM EM analysis are imported into the structural analyses, in order to evaluate the effect of such loads on the cassette structure. Problems dealt with concern the difference of meshes’ specifics and the varying of load interpolation settings.

Technologies such as Augmented Reality and Virtual Reality (AR-VR) are changing the way to design the models. These technologies prove useful across all design phases, yet their greatest application lies in supporting the entire life cycle of a system. They shine during maintenance operations and training sessions, effectively teaching operators intricate procedures.The Virtual Reality is a useful technology in the nuclear fusion field, where the immersive visualization scenarios can be applied in to simulate maintenance operation to be conducted in radioactive environment.This study was applied on the ITER Water-Cooled-Lead-Lithium Test-Blanket-Module (WCLL-TBM) ancillary systems. The performances of the virtual reality have been tested simulating an entire maintenance operation, focusing on three main parameters: i) time, crucial aspect in nuclear field where is important to reduce the exposition to the radioactive material; ii) obstacles identification, to avoid interference with other objects during maintenance operation; iii) ergonomic standard, to consider all ergonomic parameters like the mass of the object and the verify of a correct position of an operator in each single operation.A maintenance simulation has been developed through use of a Virtual Reality tool (HTC-VIVE pro-2).

The conceptual design stage is one of the main challenging phases in System Engineering. Starting from the High-Level Requirements (provided by the project needs), defining the broad features and conditions that a product must ensure, different design solutions are often implemented. Several methodologies can aid whenever a decision-making process has to be performed. Among these, the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) stands out, providing a rational framework for a needed decision by quantifying its criteria and alternative options, and for relating those elements to the overall goal. Fuzzy AHP centralizes the opinion of experts who, through objective and subjective opinions, can rank the conceptual alternatives. The paper deals with the assessment of components for thermonuclear reactors, in particular the design of the DTT Divertor In-Vessel Fixation System. The main requirements that the Fixation System must guarantee are strictly related to the geometric-dimensional constraints concerning the presence of the various in-vessel components. Furthermore, the Fixation System must withstand the strong loads acting on the Divertor due to the partial or full loss of plasma confinement (Disruption Events). The aim is, therefore, to identify, through Fuzzy AHP, among different alternatives, the solution which best matches the functional requirements, geometrical constraints and Remote Handling compatibility.

A physical Remote Handling (RH) test facility can play a key role in the Verification & Validation phase of the design and development of the Remote Handling System (RHS) of a fusion reactor and of the reactor itself. This key role is described in this paper, highlighting the achievements reachable in such a facility in support of the fusion reactor design and reporting the experience gained in the leading RH test facilities developed in the last decades. In the end, the project of an innovative RH test facility for fusion reactors, aimed at overcoming the limits of the already operative ones and the still present obstacles in the related scientific fields, is presented.

The challenge of the quest for energy from fusion is being addressed in the EU through a significant programme articulated in a roadmap combining the design of a Demonstration Fusion Power Plant (DEMO) and substantial R&D activities. Following the recent transition of the DEMO project to Concept Design phase, emphasis is being put on ensuring self-consistent integrated DEMO plant design concepts emerging from a system-oriented approach. A staged design approach has been adopted and the various elements of its foundation are currently being pursued. The paper provides an overview of the organized effort leading to the development of a concept for the maintenance of the breeding blanket of DEMO as an example of the overall process of concept selection and concept validation laid out for the DEMO Concept Design phase. This specific effort is done in a collaborative framework with the China Fusion Engineering Test Reactor programme that seeks to resolve the same issues on the way to a first-of-a-kind fusion power plant.

Nuclear fusion facilities, as tokamaks, are very complex devices, due to the harsh environmental conditions required to maintain the plasma advance confinement scenarios and the deuterium-tritium fusion reaction (huge temperatures, nuclear radiation, extreme electromagnetic loads). Therefore, several specific concerns shall be considered during the design process of a tokamak, and appropriate solutions shall be designed and provided. These concerns are treated in this paper and some of their possible solutions are explained. This is done following the flow of good practice design process, focusing on each stage from the material selection to the component procurement.

This paper illustrates a methodology for evaluating the Dynamic Amplification Factor (DAF), useful to assess the structural behaviour of the DEMO divertor under electromagnetic loads. The purpose is to determine a conservative DAF in order to justify the usage of DAF-amplified static analyses instead of more demanding (from a computational point of view) dynamic analyses, allowing for faster structural assessments and optimization processes. The proposed approach allows to amplify the structural quasi-static response conservatively, to estimate the maximum dynamic response. The methodology is of general validity and can be used even when some relevant variations on the structure are made.

In this work we briefly review some of the current available solutions of long reach manipulators that have been or are serving as robotic equipment for remote maintenance in fusion reactors. These robotic equipment are long reach since they are intended to access inside the fusion reactors through small–scaled access ports and are designed to remotely install/replace in-vessel mechanical components within the reactors. We start the work by analysing the design criteria commonly used and the most interesting concepts from the authors’ perspective, where we found a general scheme that could be adopted for the most cases when we study this kind of robots. Finally we present a discussion and draw our conclusions.

The Product Lifecycle Management (PLM) systems lead the development of a product or a system from the early concept design until the end of the life allowing the knowledge management step by step. Among these systems, the 3DExperience platform adopts a Model Based Systems Engineering (MBSE) approach and allows to implement each phase of the design in a single co-simulation environment. This platform has been chosen for the development of the Divertor Tokamak Test (DTT) facility. The DTT tokamak, under construction at ENEA site in Frascati, has the main aim to contribute to the development of a reliable solution for power exhaust in a reactor, one of the major issues in the roadmap towards the realization of a nuclear fusion power plant. The divertor is one of the most challenging systems whose requirements coming from different physics and interfaces shall be balanced. The fixation system is the interface between the vacuum vessel and the divertor cassette body whose concept design has been carried out in a PLM system. This paper deals specifically with the application of the Requirement, Functional, Logical, Physical (RFLP) approach to the DTT divertor fixation system from the requirement elicitation and definition until the preliminary physical design, implementing each phase in the 3DExperience platform.

As vehicles have become more complicated, Human-Machine Interaction (HMI) is becoming crucial. Nowadays, HMI is a substantial element in autonomous vehicles (AVs). Numerous studies are lately being published regarding significant parameters of AVs which can affect HMI. Hence, it is imperative to have a comprehensive prospect, to improve people’s acceptance of AVs. In AVs, the driver’s role will change to a passenger, however, it can be switched in some special situations. This work is divided in two parts: the first study has mapped from 299 papers in this area and found the most impressive concerns of people in using AVs. Regarding the researchers’ expertise and aim(s), each study has investigated the interactions between human and vehicle from a specific facet. In general, it can be claimed that a dramatic shift from physical parameters to psycho-emotional ones can be observed in recent years. The results showed that trust and comfort are ranked first and second in the reviewed articles, respectively. The second part is dedicated to the explanation of methodology, the synthesis of findings and the perspectives about the future scenarios. Finally, a novel model named 3p is proposed which includes personal, psycho-emotional, and physical parameters, and states the current trend of momentous features affecting HMI in AVs.

Now a days new products are evaluated in the initial phases of product development in order to identify all design problems as early as possible before the prototype or manufacturing of the product. With advent growth in innovative technologies, simulation and testing of the human centered product designs are being performed using digital models & immersive to semi-immersive environments. There are numerous concepts and methods for this purpose, which have evidently proven to be effective solutions, such as Digital Human Modelling (DHM) or Human Model in the Loop simulations (HMITL), to facilitate ergonomic evaluations without interactions, and Virtual Reality (VR) technology to enable Human in the Loop (HIL) simulations in immersive environments along with interactions. These simulations are performed utilizing various software, which makes the data integration phase a complicated and time taking process. This paper elaborates on a new approach of adapting DHM analysis in a VR simulation for analyzing living space inside a 3D model using a single open-source platform, UNITY 3D. This process is expected to reduce the need for multiple programs during simulations, thereby reducing costs and time while providing uncomplicated visualizations. A use case scenario in view of assessing living space inside a novel aircraft lavatory design with baby table integration is also presented. This paper serves as a step towards inclusive design analysis and predicts its potential in various fields to study ergonomics and interaction of products at the early stage of product development.

Drivers are generally good at anticipating driving situations. They use implicit cues, such as lateral and longitudinal movements of other vehicles and contextual cues such as characteristics of the prevailing situation. These cues also help drivers in adapting their driving behaviour, such as whether or not to cooperate on the road with other road users in a specific situation. Predicting the intentions of other road users using these cues is also important for automated vehicles: i) to facilitate accident-free and smooth driving ii) to improve cooperation with other road users, and iii) to adjust manoeuvre behaviour depending on the dynamic situation when interacting with other road users To investigate different manoeuvres performed in a specific scenario in combination with systematically varied implicit and contextual cues, we conducted a driving simulator study on a highway consisting of twelve on-ramp situations with 36 participants. To gain a deeper insight into the driver’s perception of the cooperativeness of the automated vehicle depending on the chosen strategy, we used the thinking-aloud method and interviewed the participants after the experiment. Additionally, participants rated their experienced trust and acceptance of the manoeuvre design after each situation.

As vehicles have become more complicated, Human-Machine Interaction (HMI) is becoming crucial. Nowadays, HMI is a substantial element in autonomous vehicles (AVs). Numerous studies are lately being published regarding significant parameters of AVs which can affect HMI. Hence, it is imperative to have a comprehensive prospect, to improve people's acceptance of AVs. In AVs, the driver's role will change to a passenger, however, it can be switched in some special situations. This work is divided in two parts: the first study has mapped from 299 papers in this area and found the most impressive concerns of people in using AVs. Various researchers’ approach has shown a dramatic shift from physical parameters to psycho-emotional ones; as results, trust and comfort are ranked first and second in the reviewed articles, respectively. The second part is dedicated to the explanation of methodology, the synthesis of findings and the perspectives about the future scenarios. Key findings and some insightful observations on the future of this approach are discussed in this section of the article. As a conclusion, we developed a novel model named 3p consisting of personal, psycho-emotional, and physical parameters, which states the current trend of momentous features affecting HMI in AVs.

This paper aims to highlight the importance of Computer-Aided Design (CAD) model integration within multi-domain modelling activities. Information about geometrical system size is generally lost in a multi-domain numerical model that focuses on simulating the interactions among different physical system parameters during their operations. For this reason, the present paper proposes a multi-domain modelling approach that uses both geometrical and numerical models to study the behavior of a battery electric vehicle (BEV) energy storage system (ESS). In particular, the numerical model is aimed to simulate thermo-electrical ESS behavior in MatLab/Simulink environment while the geometrical CAD model supports the design activities of different battery cells layout using SolidWorks Dassault software. The objective of this integrated model is to compare the Battery Pack (BP) hotspots of the different designed layout solutions obtained. In conclusion, four different layout solutions have been proposed and compared with some evaluations related to their geometrical size, to test the effectiveness of this multi-domain instrument.

Extended Reality (XR) applications require Photorealistic Virtual Prototypes (PVPs), usually obtained by generating a polygon-based textured model of the original CAD (Computer Aided Design). Getting PVPs requires specific rendering and texturing software tools that experienced technicians use. Automatic simplification and conversion approaches from CAD to XR exist but are almost all focused on models without textures. The paper aims to establish a semi-automatic method for creating low-poly PVPs for XR starting from 3D CAD models. The process, implemented in Blender, consists of several steps. First, starting from a high-poly model imported from a 3D mechanical CAD system, the modelling cage (a low-poly simplified version) is designed. Second, a low-poly variety of the CAD geometries are generated using Blender modifiers (i.e., shrinkwrap, subdivision surface and Boolean). Texture mapping is carried out on the cage. Then, by combining Shrinkwrap, Boolean and Subdivision Surface modifiers, the cage is projected on the CAD-imported high-poly model. Thus, it becomes a low-poly version of the same geometry. Finally, the Normal Baking process adds high-frequency details (e.g., engravings). Thanks to the generation of a UV-Mapped cage wrapping up the component, in case of local modifications to the latter, Blender semi-automatically updates the PVP. The method was used on three stock versions of a sporting rifle. With an average duration of 23 min, the proposed approach more than halved the time required with manual modelling techniques.

Synchronizers are mechanical devices used in gearboxes for braking the fastest shaft up to the angular velocity of the slowest one before engagement. Nowadays, many dual-clutch transmissions include an increasing number of gears in order to improve vehicle performance. However, they still use established and stable solutions for the synchronizers, counting a large number of parts to be manufactured with tight tolerances, and wide axial dimensions. So, the reduction of the synchronizer length is an important goal for the design of new gearboxes with a larger number of gears. The present research work studies a new solution for a shorter and simpler synchronizer. The main innovation is that the traditional conical clutch is replaced with a plane clutch including dog teeth, so that one part is performing both tasks of synchronization and engagement. The present paper discusses a first attempt dimensioning of the synchronizer in order to evaluate its feasibility. The layout was developed interactively with conceptual CAD models for representing the functionality of each element and with 3D printed prototypes in an electro-actuated test rig. This new synchronizer mechanism can be used in new dual-clutch transmissions, with electro-mechanical actuation and possibly with additional speed sensors.

Recent advancements in additive manufacturing technologies have significantly enhanced the capacity to accurately reproduce the shape and material properties found in nature. Furthermore, the behavior and functionality exhibited by natural systems can be effectively simulated using bio-inspired algorithms. An essential parameter that governs various life processes is the surface area to volume ratio. In industrial applications such as catalysis and heat exchange, this particular characteristic is intentionally augmented to enhance overall performance, thus fulfilling the functional requirements.In this study, a curve differential growth implementation was developed to obtain space-filling and self-avoiding paths. By applying successive iterations of the algorithm to an initial curve, a set of curves was generated. These curves were then organized in three-dimensional Euclidean space and combined into a NURBS surface. As a case study, the design of a coaxial counterflow heat exchanger employed the proposed modeling algorithm. The resulting model underwent a numerical simulation to assess the heat transfer rate and pressure drops. Material extrusion technology was used to manufacture a prototype for preliminary demonstration, although further studies are required to ensure watertight functional parts. Numerical results indicate that the proposed design exhibits a better heat transfer rate in a smaller size but leads to higher pressure drops when compared to three equivalent plain pipe solutions (with matching length, surface area, and heat transfer rate).

Multi-material additive manufacturing enables the opportunity to combine multiple materials within the same part, allowing for an expanded range of properties that can gradually change inside the design space.This category of materials is commonly referred to as functionally graded materials (FGMs). However, FGMs currently face several limitations and challenges in terms of design and manufacturing, such as compatibility, distribution design, and prediction of mechanical properties. Furthermore, when dealing with parts possessing complex micro/meso-structures, finite element simulation often becomes a costly and time-consuming process.Among various additive manufacturing technologies, fused filament fabrication allows the combination of multiple thermoplastic materials within the same nozzle during the deposition process, thereby creating FGMs.This process, known as coextrusion, enables the gradual deposition of materials adjacent to each other while changing their fractions. Moreover, the deposition direction shapes the distribution of materials within each deposited layer, influencing the material structure and the resulting mechanical properties. A recent study proposes a preliminary model describing the deposition mechanism, which has been confirmed by experimental tests. This model delineates the section of the material deposited based on the tool path and process parameters, such as layer thickness and hatching space.To expand upon these findings, this paper applies a homogenization approach based on finite element analysis to the deposition model. This approach enables the description of material mechanical properties based on the material fractions, tool path, and other process parameters. Additionally, this study presents a methodology to tailor the mechanical properties according to the printed part’s orientation around the print bed.

In recent years, many industrial companies have embraced new technologies for Industry 4.0, the fourth industrial revolution. This global manufacturing trend connects real-life industry with the virtual world. Digitalization tools play a crucial role in allowing companies to decrease design and production costs, as well as accelerate the product development process. Regarding an actual industrial case study of an Italian automotive company, this work focuses on the use of digital technologies in designing complex manufacturing systems, showing the benefits that can be obtained with respect to traditional methods. Digitalization tools have aided in the design of intricate manufacturing systems that demand advanced automation to optimize the arrangement, workflow, and equipment configuration within a manufacturing facility or production line. After examining the features of the virtual approach employed by the considered company, the virtual commissioning of a screwing station for an electric axle assembly line is analyzed in detail to show the efficiency and effectiveness of digitalization.

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.

This paper discusses the integration of Industry 4.0 technologies in manufacturing facilities to implement the Smart Factory paradigm exploiting Cyber-Physical Systems, Internet of Things, Big Data and Cloud Computing as key enabling technologies (KET). The study aims to define a methodological framework to design and implement connected machines to realize the Smart Factory model by interconnecting the KETs through the pragmatically implementation of digital twins from design to production.The study fills a literature gap by formalizing an approach for studying and implementing digital twins for value creation from a servitization perspective. The approach is illustrated through a successful case study and represents the first results of a long-term research project funded by the Italian Minister of Economic Development. Future works will expand the approach to more case studies to provide formalized guidelines of general applicability.

Computational image aesthetics aims at determining what makes an image look pleasing. Assessing image aesthetics usually relies on the extraction of suitable image features related, for instance, to image composition (e.g. rule of third, depth of field), texture, shape and colour. It is widely accepted that colour, in particular, plays a major role in this context. The objective of this study was to investigate potential relationships between the most significant colours in an image (the colour theme, or palette) and the aesthetic rating. To this end we defined a procedure for colour palette extraction and its characterisation by a set of 21 hand-crafted features. Rank-based correlations between the features and manually-assigned aesthetic ratings were assessed by Spearman’s correlation coefficient. Experimenting on a total of 4,647 images from the public dataset EVA we found that 12 features were significantly associated with image aesthetics, although the overall correlation strength was at best weak. In particular, perceived aesthetic rating correlated positively with saturation (indicating a slight preference for colourfulness) and negatively with colour temperature (suggesting a slight preference for warm colours). A significant positive correlation (but again weak) also emerged between perceived aesthetic and harmonic colour schemes.

In mechanical design, tolerance stack-up has a fundamental role to ensure mechanical coupling among assembly components. To avoid interferences, gaps between connected parts are introduced since the design phase, to compensate for possible dimensional variations. The present study aims to assess clearances in the Volkswagen Crafter chassis, by comparing the CAD model to the 3D reconstruction of the real van, obtained by means of 3D scanning. This activity has been carried out within SMART AMBULANCE project (POR FESR Toscana call), which has as its goal the realization of an advanced ambulance by implying smart technologies. Clearance analysis was performed before proceeding with the design of the interior setup of the ambulance medical compartment, since even small deviations may compromise the assembly of the covering panels. The analysis was useful not only to evaluate deviations between ideal and real geometry, but also to identify the locations of the gaps.

The treatment of burn scars is a hotly debated and delicate subject since ineffective therapy can significantly lower quality of life. Ideally, medical evaluation should leverage objective assessments of progress over time to provide an adequate assessment of scar health and related treatment. In contrast, common clinical practice involves medical examination that rely on subjective assessment scales such as Vancouver Scar Scale and the Patient and Observer Scar Assessment Scale. Recently, extraction of objective parameters for the investigation of scar surface were studied by objectively analyzing the surface topography and extracting scar roughness through a transposition of standard mechanical surface evaluation methods, which are based on ISO 4287 and ISO 4288, to the clinical field. The most advanced methods analyze the scar roughness globally and after subdividing it in sub-patches of pre-fixed dimension. In both cases, it is not considered that the scar may be located in non-planar portions of the body, therefore, roughness values are dependent from the principal roughness evaluation direction. In the present work these shortfalls are overcome using a systematic procedure to subdivide the patches in a consistent manner and analyze smaller portions of the surface providing a roughness value independent of the filtering direction.

For the more than 100 years forensic firearm identification has been conducted by examining physical evidence under the optical comparison microscope. Nowadays, 3D technology offers advanced and powerful tools that deserve to be considered to evaluate a new and different solution for processing ballistic data. The method proposed in this work is based on the processing of the 3D point clouds of the cartridge case back. It starts with the transformation of the point clouds of the bottom of the cartridge case into a 64-bit greyscale image. The second step is to use a polar derivation technique for exploiting the polar characteristics of the features impressed on the cartridge and also to overcome the problem of the initial orientation of the cartridge. The dataset used for the experimental part was made by Messina Carabinieri Scientific Investigation Department (Italy) and it contains point clouds of several cartridge cases acquired with an Automated Ballistic Identification System (ABIS). After the pre-processing, the method has been tested with SIFT to verify the invariance on the feature extracted. Although not yet ready for forensic applications, the method appears to be promising and innovative to be applied in the common pattern recognition process in this field.

Survey missions in the underwater environment are key activities in several application fields, but the physical properties of such a harsh environment make it challenging for both navigation and data collection. In particular, in the field of underwater photogrammetry, optical sensors are mainly installed on remotely operated vehicles (ROVs). The maneuvering is performed remotely by expert pilots who can only rely on bidimensional visual feedback from one or more camera streams. Additional navigation data can aid pilots in assessing if the mission meets the requirements while undergoing it. To this end, the paper presents a SLAM-based solution that can be used to compute parameters in support of ROV pilots during photogrammetric surveys, when a stereo-camera is equipped. In order to assess the performance of the proposed solution, different tests were conducted. These tests involved comparing the parameters derived from SLAM with the data computed by the navigation system of a professional-grade ROV. The focus of this comparison was on three key parameters: position, velocity, and distance from the target.

The present work proposes the use of point clouds differential entropy as a new method for reverse engineering quality assessment. This quality assessment can be used to measure the shape deviation of objects made with additive manufacturing or CNC techniques. The quality of the execution is intended as a measure of the deviation of the geometry of the obtained object compared to the original CAD model. The method exploits the quality index of the CorAl method. The advantages of CorAl are several, among them the use of a unique index of comparison, no problem of commutativity of the comparison, noise immunity, low influence of the presence of holes and of the point cloud densities. It is possible to plot quality maps showing the areas with the greatest deviation. In experiments, objects obtained by additive manufacturing with different print qualities are tested. The robustness of the method is also demonstrated. The quality index evaluated for each object, as defined in the CorAl method, turns out to be gradually closer to 0 as the quality of the piece’s construction increases.

The alignment of large datasets associated with 3D reconstructions is still an open issue in the scientific community. Among the several strategies available in the literature, some are based on using geometrical features. In this paper, the Authors have investigated the reliability of associating ideal planes with non-ideal roof features, which may be used to realign 3D terrestrial reconstructions. The obtained results underline a deep influence from noise, which affects the non-ideal roof feature and ideal plane association, and the necessity to define additional experiments to confirm the robustness of the solution.

Augmented Reality (AR) is considered one of the key pillars of Industry 4.0 as it innovates the manufacturing process and promotes new ways of human-machine interaction. Among the main challenges influencing the implementation success of AR technology in industry, visualization modalities of AR content represent a crucial factor to be considered in relation to the application domain. In this regard, previous studies evaluating different AR-based content visualizations have demonstrated significant implications on worker performance and, in particular, specific factors such as colors applied to virtual information and uncontrolled environmental conditions, which can hinder the correct perception of AR content by users. Based on these considerations, the paper proposes a context-aware recoloring approach for AR-assisted maintenance applications for both indoor and outdoor environments. More specifically, the proposed approach is used to recolor virtual information on the basis of real work conditions in order to improve distinctiveness and visibility of virtual objects with respect to the real ones. By way of example, a use case is presented for exploring the benefits of the proposed solution in the field of maintenance activities. The outcomes provide the basis for further improvement and experimentation in a real industrial setting.

Dental tool positioning is a challenging manual operation that requires precise 5DOF positioning of the drill -rotation around the tool is not influential- minimal error can result in grave consequences such as nerve and bone damage. Augmented Reality (AR) can help to assist tool positioning, but the widgets proposed in the literature are quasi-static, commonly using virtual 3D cylinders or lines to be visually collimated and eventually supported by color change. We draw our inspiration from the photographic viewfinder and propose a novel Virtual Stigmometer Widget (ViSti) to convey tool positioning error magnitude to the dentist. The widget slightly blurs the view and gradually focuses it while approaching the target (i.e., implant drilling position) till it is perfectly collimated. We conducted a within subjects experiment (N = 30) to compare our widget with the golden standard in 32 positioning tasks. NASA-TLX results demonstrated that our widget reduces frustration (−43%), and mental demand (−19%), and the user perceives a better performance (+8%). However, the expected tradeoff is effort (+34%), and physical (+33%) temporal demand (+4%). Our widget demonstrated to have a potential usage for dentistry and in further fields where 5DOF precision is crucial.

In response to the increasing number of traffic accidents, industrialized countries are investing in educational programs to raise awareness of safe driving. The most common type of intervention to reduce risky driving behaviors is the showing of traumatic experience videos related to the occurrence of traffic accidents caused by incorrect and high-risk driving habits. However, the effectiveness of this intervention depends on several factors, including how this content is experienced. Nowadays, thanks to Cinematic Virtual Reality (CVR) technologies, new modalities of video content fruition can be exploited. In this work, we implemented a CVR application to show 360° videos of traffic accidents and evaluate the effectiveness of CVR as an educational intervention tool to improve drivers’ attitudes toward traffic safety. A sample of 86 users aged 18 to 56 years answered a questionnaire on Attitudes Toward Traffic Safety Scale (ATTSS) administered before and after the CVR experience. In addition, a user experience questionnaire (UEQ) was administered. The results analysis of ATTSS questionnaires shows that the CVR experience increases risk awareness by inducing greater attention to safety while driving. Finally, the results of the UEQ questionnaire reveal that users positively evaluate the experience of using the system from hedonistic, pragmatic, and usability perspectives.

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.

Using custom-made physical cutting guides in maxillofacial surgery presents several drawbacks, mainly related to design, time, and costs. Even if the literature provides several Augmented Reality (AR) solutions, they mostly display cutting planes and static assistance for repositioning. This work proposes a Mixed Reality (MR) application, deployed on Microsoft HoloLens2, to guide the surgeon in maxillofacial osteotomies and repositioning through intuitive and interactive digital content. A holographic panel allows selecting between the osteotomy and repositioning modes. With the first one, the cutting lines and the drilling points for the fixation plates are overlaid on the patient’s skull. With the second one, three different kinds of feedback simultaneously guide the surgeon toward the correct final bone placement, step-by-step, according to the real-time fragment displacement. The MR app was tested by seven inexperienced subjects using a 3D-printed skull. Satisfactory results were obtained for maxillary osteotomy (i.e., less than 1.5 mm deviations) and relocation (i.e., the accuracy is about 0.7 mm and 0.6°).

This work aims to propose a virtual mirror as a tool for an Augmented Reality (AR) interface in support of operators who perform maintenance tasks, especially in blind areas with component occlusion. In the literature, it is still not clear what is the best AR solution to help workers perform maintenance tasks with occluded components. Thus, we designed an AR interface with a virtual mirror that can assist workers in identifying occluded components thanks to an additional workspace viewpoint. While physical mirrors are commonly employed in maintenance tasks to address blind spots, virtual mirrors are not yet widely adopted. Therefore, our study intends to design and evaluate a virtual mirror that simulates workers’ behavior using a real one in maintenance tasks. We planned a user study to compare the real and virtual mirrors in a real maintenance context. We conducted a performance evaluation with 20 users. Findings indicated no statistically significant differences between the virtual and physical mirrors regarding completion time, accuracy, and cognitive load. Our solution makes it possible to replace a real mirror providing the same user performance but with the advantage of being able to place it without space limitations and observe additional information exploiting AR.

Over the decades, technical documentation has moved from paper to digital, until today in which operators, through Augmented Reality (AR), have the possibility to be helped in component location and recognition for different procedures. To support these activities, AR interfaces need to be developed with instructions provided through visual assets tailored to the information to convey. For localization tasks, auxiliary models, i.e., standard geometric shapes are the most suited. In this work, we propose ADAM (Automatic Development of Auxiliary Models): an authoring tool to support designers in generating various shapes of auxiliary models in the right dimensions and without modeling them in a CAD software. Thanks to this tool, the designer has a ready-to-use database of auxiliary models to choose from reusable in different AR technical documentations. In this way, ADAM allows to significantly reduce the time spent creating each auxiliary model from scratch. We validated our tool in a user study. A focus group of expert designers were asked to implement an AR interface, using auxiliary models for a localization task, with both ADAM Tool and the current authoring practice. The results confirmed that our tool outperforms the current authoring practice in terms of time performance and user experience.

This paper introduces a unique, feature-based methodology for determining the best design features of a Virtual Reality Training System (VRTS). It offers a holistic approach by using a revised Technology Acceptance Questionnaire, which assesses design features from a user's perspective, rather than relying solely on objective measures of training effectiveness. We implemented the methodology in an experimental campaign, which involved simulating manual processes in two VR platforms with different features. Both novice and experienced VR users participated in the study, evaluating design features for perceived usefulness and ease of use. The findings provide insights into improving VRTS design based on user experience, highlighting the potential of our feature-based methodology.

The growing importance of the human-centric perspective, emphasized by the transition to Industry 5.0, and the diffusion of the mass customization paradigm increase the need for methods and tools to support the user-centered design (UCD) and prototyping process. Key enabling technologies (KETs) of Industry 4.0 are a valid support for the pursuit of this goal. X-Reality can assist in analyzing customer needs and translating them into technical specifications by involving the customer in the design review through an immersive user experience. However, X-Reality design often lacks a human-centered approach. The proposed work aims at addressing this by using virtual simulation for the UCD of the X-Reality experience, ensuring it is immersive, safe, ergonomic, and comfortable for the user. A case study of an Italian company that produces sporting rifles, for whom developing high perceived value products is crucial, is used to demonstrate this approach. A dedicated area of the company plant was designed to host two types of X-Reality experiences to test the prototype's functionality and aesthetics with customers. They consist of a mixed reality application, which involves the use of a head-mounted display and haptic gloves, and an augmented reality application provided by a projection system.

One key aspect of the fashion industry is the presence of small manufacturing companies and their need to present a sample collection to the reseller and find wholesalers. This Business-to-Business (B2B) activity is characterized by complex storytelling and communication methods to convey the value of the products: materials, finishes, sizes, and fit options. Usually, the showroom is used to present the garment collection, a representative of the manufacturer, and one or more resellers. Setting up a physical showroom is expensive and requires the transportation of the entire collection. During the pandemic, when physical interactions were severely limited, companies had to adopt alternative solutions by using the Internet to communicate with other companies. By the end of this period, the use of such solutions proved to be extremely convenient and practical. We present a Metaverse-based showroom, that differently from the literature focuses on B2B fashion showrooms instead of direct sales or retail. We based on the VRChat and used Head-Mounted Displays (HMD) to recreate a real-life showroom. The users are remotely seated at a shared desk in front of the catwalk. The reseller can interact with the following functions: collection presentation, fashion show participation, and material/color configuration. We conducted a user study with 10 expert subjects, simulating two remote-selling scenarios of a jacket collection from a partner company with real experienced sellers and distributors user and assessing the user experience measurement. The user test is measured with the User Experience Questionnaire (UEQ). The results showed positive evaluations in terms of attractivity, apprendibility, stimulation, originality, and positive outcomes regarding sustainability.

This work proposes a Mixed Reality (MR) application, designed for HoloLens 2 which enables seamless interaction between collaborative robots and human operators, regardless of their prior experience or expertise in the field of robotics. Building on the application presented in a previous work of the authors, the novel contributions are focused on a bi-directional interaction that manages the exchange of data from the robot to the human operator and, in the meantime, the flow of commands in the opposite direction. The robot-to-human flow consists of the information about the robot state (joint positions, velocities and torques), the distance from the joint limits and the planned path of the end-effector. Moreover, the human commands to the robot the desired end-point for the end-effector, than the planned path can be directly modified by moving a set of way-points displayed in the mixed reality environment. A Franka Emika Panda collaborative robot has been used to test the application.

Extended Reality (XR) has experienced rapid growth in the past decades, proving to be a viable alternative to conventional practices in all the fields. Professional VR solutions have been developed; giving people access to virtual scenarios that are very similar to their real counterparts owing to the high level of realism reached with the latest technologies. Wearing a VR headset, the users can explore spaces they’ve never been before in real life, getting familiar with them without the dangers of the real-world circumstances. This principle paved the way to X-Reality development in the context of training for harmful procedures in many professional fields, and medicine makes no exception, being particularly involved in searching for novel methods to educate experts.This research explores the potential of X-Reality in medical training, proposing an innovative virtual training system to let medical personnel perceive ionizing radiation in a virtual scenario. The virtual environment was reconstructed with photogrammetry and within it users are able to fix their bad habits related to radiation exposure during an orthopedic surgery.To improve the XR system’s effectiveness a short beta test was set up involving medical experts, with some interesting regarding the benefits and issues of the XR system.

This research responses to major challenges in the development and commissioning of multi-robot systems. A mechanical coupling through a handled workpiece may result in damage to the piece or the entire system when the distance between the robot TCPs deviates during motion. This paper introduces a novel method that allows to successively test and characterise a newly developed multi-robot control systems. It identifies the impact of control errors and geometrical deviations using a hardware-in-the-loop (HiL) setup in one, and a real robot system in another step. For this purpose, the distance between the TCPs is measured during HiL- and corresponding demonstrator experiments. Thereby, the method provides a foundation for a novel multi-stage characterisation process. This enables conclusions about the causes of errors in control programming, model quality, and geometric deviations.

In this paper, we use the Discrete Element Method (DEM) to model the switchable stiffness behavior of components for robotic structures. These components are built-up with an elastic cover and a granular medium. By means of vacuum pressure, the jamming of the particles, and therefore the stiffness behavior, can be adjusted. Aim of the model is to predict the structural behavior of such components considering size scaling effects. The model is compared to experimental results of a bending test. Main challenges of using the DEM for such a configuration is the mapping of the elastic cover and the load application. The load application can be realized by coupling with a multibody dynamics system using the Functional Mock-up Interface. For mapping the cover, the elasticity has to be adjusted because of numerical discrepancies. The comparison with the experimental results shows that the influence of the cover elasticity is negligibly small. The differences between simulation and experiment can be explained by the particle shape. To save computing time, sphere shapes are considered for the model, but the real particle shapes are sharp-edged polyhedrons. With the model the influence of parameters such as dimensions, filling degree and vacuum pressure can be determined.

In this paper, two concepts of silicone–based pneumatic soft bending actuators with stiffening capability are presented and compared in terms of performances and sustainability. The first concept is a PneuNet bending actuator with a vacuum chamber, while the second one is a Fiber–reinforced bending actuator, again with a vacuum chamber. Both soft actuators are able to perform a bending movement and are able to increase their stiffness through layer jamming. The two concepts are first compared in terms of overall performances, namely bending behavior, capability to exert tip forces and stiffening capability. After, they are compared in terms of sustainability, through the analysis of the energy that they require for movement execution.

Soft robots are increasingly advancing into heterogeneous contexts, however they still suffer from different sustainability issues including limited lifetime, disposal and poor energy efficiency. These issues severely limit their spread usage thus leading to the need for new materials and efficient actuation systems. The main goal of this work is to find out in scientific literature the main indicators concerning environmental sustainability in pneumatically actuated soft robots. To reach this goal, we used the PRISMA methodology to explore, in a systematic manner, available indices related to environmental dimension of sustainability. The indicators found are reported with the absolute and relative metrics adapted from the references and two proposed categorizations: i) one related to the part of soft robotic system, ii) the other one related to the LCA-oriented Product Lifecycle (PL) phase. The study highlights the lack in the literature of indicators related to energy consumption regarding environmental dimension of the manufacturing process, thus opening the possibility of future studies in this direction.

Soft microrobots have gained great attention in the bioengineering field due to their ability to navigate into biological fluids, overcoming biological barriers. Indeed, thanks to the size and controlled movement they can easily deliver drugs to a specific target.In this work, we present completely natural and biodegradable propulsion soft micro-robots made of alginate, in the shape of microparticles (MPs). These MPs have been loaded with sodium bicarbonate and are meant to be delivered together with citric acid as a powder-based formulation embedded into a capsule that will open in the gut. Sodium carbonate released from MPs allows a propulsive action due to the citric acid spherical gradient established upon its release, making MPs go radially toward the gut mucosa. In principle, MPs can be loaded with anti-inflammatory drugs or probiotics allowing a slow release of the compound close to the cell layer. The action of such micro-robots was tested inside a microfluidic device that recreated citric acid gradient, with a channel for the introduction of MPs. Here we saw the propulsion activity of MPs towards lower citric acid concentration by taking time-lapse images. Caco-2 cells were cultured in the same microfluidic device allowing the formation of a mucus-like layer to assess the accumulation of the propulsive MPs.