Product design and engineering

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

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

The high-performance car industry demands increasingly lightweight and durable components, driving the development of innovative manufacturing techniques and increasingly high performing materials. Among critical automotive components, mechanical hinges with close supports play a key role in ensuring high functionality in limited spaces while contributing to the structural efficiency and safety of vehicles. This study examines an accurate design and manufacturing process for hinges with close-range bushings. In particular, the manufacturing technology of the Polytetrafluoroethylene (PTFE)-coated bronze bushing connected with a FeZnNi pin inside the hinges was analysed and optimised. A predictive mathematical model was developed and validated with measurements using an appropriate experimental set-up created by the authors. Specifically, the experimental tests were performed by simulating and automating the rotation of the hinge; this made it possible to accurately assess the resistant torques due to assembly errors, tightening torques, geometric and dimensional tolerances. Through the proposed methodology, the resistant torque was related to the correct manufacture, the PTFE coefficient of friction, and the operating temperatures, guaranteeing long-lasting performance and reliable integration of hinge components. The results demonstrated that the proposed methodology enhances the manufacturing process by allowing the production of reliable and high-performance mechanical hinges.

Keywords: Fe-Zn-Ni alloy , Geometric and dimensional tolerances , Long-lasting performance , PTFE-coated bronze bushing , Resistant torque

Maintenance activities on transportation infrastructures, particularly on the underside of bridges and viaducts, present critical challenges related to safety, accessibility and cost-efficiency. Conventional solutions, such as scaffolding or mobile platforms, often exhibit substantial operational limitations. In this context, modular articulated robotic arms present a promising, safer, and more flexible alternative. This study introduces a functionality and data-driven design methodology for the modular development of articulated robotic arms specifically tailored for bridge maintenance applications. The proposed approach integrates Finite Element Analysis with clustering algorithms to identify mechanically equivalent joint modules based on their structural response under realistic loading conditions, including self-weight and external forces. Subsequently, topology optimisation techniques are applied to refine the geometry of selected joints, enhancing their stiffness-to-weight ratio while preserving manufacturability and modularity. Additionally, the application of Geometric Dimensioning and Tolerancing ensures mechanical reliability and precision during assembly. The effectiveness of the methodology is demonstrated through comparative Finite Element Analysis assessments between the initial and optimised designs, along with the construction of a functional prototype. The proposed framework paves the way for scalable, robust, and repeatable robotic solutions in the infrastructure maintenance sector.

Keywords: Bridge Maintenance , Clustering Algorithms , Geometric Dimensioning and Tolerancing , Modular Robotic Arms , Topology Optimisation

This paper presents a novel design-driven methodology for fabricating marine sandwich structures using additive manufacturing (AM). The approach leverages the geometric freedom enabled by Fused Filament Fabrication (FFF) to produce complex lattice cores from PA12-GF15, a fibreglass-reinforced nylon, directly integrated into sandwich panels with laminated glass fibre skins. A hull portion of the Chichester Scow dinghy was selected as a case study to demonstrate the method's feasibility. The core geometry was generated through volumetric lattice modelling in Blender, enabling full customisation of the internal structure to match the outer hull surface. The resulting sandwich panel was produced entirely in-house and compared against traditional fibreglass laminates and aluminium-honeycomb-core panels. The results show that the 3D-printed sandwich structure achieves an approximate 58,7% weight reduction compared to solid fibreglass construction, while also offering improved manufacturing flexibility and potential for performance tuning through localised lattice control. This study highlights the potential of AM in marine engineering and lays the groundwork for future research on structural behaviour and large-scale implementation.

Keywords: Additive Manufacturing , Lattice structures , Lightweight design , Marine Engineering , Sandwich structures

This study investigates differences in brain activity among thirty-seven engineering students during sketching in a creativity test and a design task. Using EEG data, we first examined the impact of baseline selection (eyes-open vs. eyes-closed) on the representation of results in terms of de/synchronization across frequency bands from theta (4–7 Hz) to lower gamma (30-45 Hz). Specifically, an eyes-closed baseline allowed for the observation of alpha desynchronization during sketching, whereas an eyes-open baseline, which better aligns with real-world design conditions, shifted the pattern to synchronization. Under the eyes-open baseline, the comparisons between the two sketching tasks revealed the following results: (1) regions that showed significant bilateral TRP asymmetries in creativity test sketching also exhibited differences in design sketching across frequency bands from theta to beta band. Areas that exhibited significant bilateral TRP asymmetry only in design sketching were located in the temporal sites (theta and beta), suggesting these areas within the corresponding frequency bands could serve as indicators for distinguishing between the two cognitive tasks. (2) Statistically significant differences between the two sketching tasks in channel comparisons were primarily observed in the theta and sub-alpha bands, especially in the left frontal and right hemisphere areas. (3) The beta band exhibited similar behavior across both sketching tasks, indicating shared cognitive processes in different sketching contexts. (4) While the lower gamma band did not show significant differences in channel comparisons between tasks, it exhibited distinct bilateral TRP asymmetry in the frontocentral area only in the creativity test, highlighting the potential of bilateral asymmetry as a more sensitive measure for distinguishing between design and creativity tasks.

Keywords: adult , article , cognition , controlled study , creativity , diagnosis , electroencephalogram , electroencephalography , human , male , right hemisphere

This paper explores proactive manufacturing repurposing as a strategic design and business opportunity beyond traditional sustainability and crisis-driven motivations. Through the analysis of nine case studies across diverse sectors, we identify key external and internal factors that influence firms' ability to repurpose components and products across applications. At the external level, market demand, technology cycles, and infrastructure compatibility shape the feasibility of second-life applications. At the internal level (design-related factors), product design features—especially modularity and life-cycle alignment—emerge as critical enablers or constraints. The findings highlight the need for cross-application opportunity assessment tools and design methodologies that balance upstream performance requirements with downstream repurposing potential. This study opens new avenues for circular design, strategic innovation, and repurposing-aware product development.

Keywords: Cross-application innovation , Design for circularity , Manufacturing strategy , Modular product design , Proactive repurposing

Despite the increasing environmental awareness, sustainable products are not routinely adopted, revealing a persistent attitude–behavior gap. While this gap has been widely studied through psychological and behavioral approaches, less attention has been given to how product design attributes shape users' perceptions and influence their interaction with products. Therefore, this article aims to explore the literature on the role of design attributes in this context, analyzing how product design attributes and sustainability cues affect user experience and product-related decisions. Based on a systematic literature review process, 52 articles were extracted from the SCOPUS database. These articles were classified and analyzed according to their main objectives. Based on the findings, attribute centrality (i.e., whether a product feature is perceived as central or peripheral to the product's identity) and product category (utilitarian or hedonic) are relevant to shape environmental attitudes and behavior. Specifically, sustainability cues tend to be perceived more negatively in utilitarian products, where functionality is prioritized, and more positively in hedonic products, where they may enhance emotional value, especially when perceived as central attributes. Therefore, these characteristics must be strategically integrated in product design to reduce the perceived trade-off between sustainability and performance. The review conclusions highlight the need for further investigation to identify how specific product design attributes resulting from the application of ecodesign principles trigger sustainability perception.

Keywords: Attitude–behavior gap , Design attributes , Product category effects , Sustainability perception , User perception

Origami-based compliant mechanisms have unlocked new possibilities in the design of adaptable structures, resulting in lightweight, reconfigurable, and material-efficient systems. However, translating the complex 3D geometries needed for practical robotic applications into fabrication-ready 2D crease patterns remains a significant challenge. The need to accurately preserve kinematic behavior while ensuring flat-manufacturability introduces additional complexity in the design process. The fabrication of origami through multimaterial extrusion additive manufacturing (MME-AM) offers a compelling solution by integrating rigid and flexible materials in a single print. Still, in turn, it poses difficulties due to the complexities related to pattern generation, its intricate assembly, unfolding, and folding sequences. To address these challenges, this work introduces OrigaMatic, a parametric computational algorithm that converts zero-thickness kinetic origami models into fabrication-ready, 3D-printable flat layouts. These developed structures can be further re-folded into their intended 3D configurations, ensuring both kinematic accuracy and structural integrity. By automating this process, the workflow accelerates the transition from concept to fabrication. It eliminates the need for manual intervention in unfolding complex mechanisms, reducing time in the design-to-fabrication process while enhancing reproducibility. The effectiveness of OrigaMatic is demonstrated by experimental validation through the fabrication of compliant prototypes, with a focus on parallel mechanisms relevant to the fields of small-scale machinery and robotics. The investigation highlights the ability of the algorithm to streamline the origami-inspired mechanism design while preserving structural integrity and kinematic functionality.

Keywords: 3D-printing , compliant mechanisms and robots , design automation , folding and origami , linkages , parallel robots

In rehabilitation, the proper use of robotic devices offers significant advantages in both safety and treatment effectiveness. Correct use specifically includes accurate positioning of the user on the device to prevent misalignments that could result in discomfort or pain, and isolation of the movement to the intended body segment to avoid compensation strategies with other joints. This paper presents the design and development of an innovative wrist alignment and locking system implemented on the EDUSA® PRO robotic rehabilitation device. The proposed mechanism enables automatic centering of the human joint, aligning the user's axes with those of the robot, and securely maintains the wrist position throughout the rehabilitation session. Additionally, it automatically adapts to different wrist sizes and user anthropometric characteristics, making it suitable for a wider range of individuals. The ergonomic design ensures comfort, ease of use, and safety, while the modularity of the system allows for application to other joints. These features help reduce setting errors by therapists and contribute to greater effectiveness and reliability of the rehabilitation process.

Keywords: Product Design , Rehabilitation Robotics , Self-Centering Mechanism

This work aims to highlight the state-of-the-art framework for implementing digital twins to support the product-process development. More in detail, the literature re-view is discussed on the base of a precise industrial context offered by a research collaboration active between the authors and ABB S.p.A., Santa Palomba (Pomezia), Italy. With this aim, applications may be distinguished by the level of complexity and related methodologies, tools and hindrances. Thanks to their prior strategic organization, data collection, processing and analytics are sufficiently mature to allow for the development and testing of various artificial intelligence and digital twin related approaches. This study identifies the key technical and methodological constraints for implementing digital twins in industrial environments, providing a foundation for future structured development. A detailed discussion of the major implementation issues is then presented, with a focus on four key areas within the specific industrial context: Process, Quality, Maintenance, and Flows. The analysis highlights both the bottlenecks and the positive aspects that can influence the effectiveness of the next future implementations.

Keywords: Data Analytics , Industry 4.0 , Integrated Product-Process Development , Machine Learning , Model Based System Engineering (MBSE)

Design thinking (DT) is increasingly emerging as an effective approach to promote innovation in educational contexts. This article, starting from an overview of the literature reviews published in the last decade, aims to outline the main opportunities and challenges associated with the application of DT in both teaching practice and teachers' professional development. The adoption of DT can contribute to improving learning experiences in all disciplines, particularly in STEM fields, by fostering more inclusive, reflective and student-centered teaching approaches. In teacher education, DT encourages a vision of the educator as a designer of the learning experience, capable of addressing educational complexities through empathy, creative experimentation and iterative problem solving. However, the integration of design thinking in school and training contexts is not without its criticalities: it requires adequate institutional support, effective scaffolding strategies and a profound change in teaching practice.

Keywords: Design thinking , Educational innovation , Student-centered learning , Teacher professional development

Coralligenous bioconstructions are biogenic calcareous structures characterized by low accretion rate and high sensitivity to natural and anthropogenic impacts. Assessing their ecological quality and health status requires non-destructive approaches. In the project “FISR 2019_CRESCIBLUREEF”, a ROV-based coring device has been developed to collect samples while ensuring minimal impact on the ecological and structural integrity of bioconstructions and overcoming scuba diving depth and safety constraints. This study evaluates whether fragments retrieved by the device are representative of whole coralligenous build-ups (“tal-quale”) for geobiological characterization at the microscale. Representativeness is assessed through (i) preservation of microfacies textures and framework integrity in thin sections and (ii) relative abundances of skeletal and non-skeletal carbonate components quantified by point-counting. The results suggested that a coring device represents a powerful tool for obtaining representative bioconstruction samples at least in terms of the relationships and distribution between different carbonate components. This innovative approach opens new frontiers in the study of bioconstructed habitats, allowing the collection of samples suitable for qualitative and quantitative analyses while preserving ecosystem integrity. It therefore represents a step toward in sustainable marine research, with great potential for monitoring, conservation, and management of benthic habitats.

Keywords: coralligenous bioconstructions , geobiological characterization , technological innovation , underwater non-destructive sampling

This paper presents a comprehensive application of an automated surgical planning workflow for bone tumor resection, integrating two previously developed algorithms into a real clinical case. The study focuses on a patient with a left tibial osteosarcoma, demonstrating how the automated framework streamlines the entire preoperative process, from tumor resection planning to allograft selection. The cutting plane optimization tool reduced manual planning time from hours to just 19 min while ensuring complete tumor removal with minimal healthy bone resection. For reconstruction, the system automatically reconstructed the patient's premorbid anatomy and selected the best-matched allograft from a virtual donor database, achieving a high degree of anatomical precision (mean distance: 0.29 mm). The results highlight the clinical potential of this integrated approach, which improves efficiency, reduces subjectivity, and enhances reproducibility in complex bone tumor surgeries.

Keywords: Allograft , Design Method , Optimization , PSO , Tumor Resection , Virtual Prototyping

Soft robotics represents a paradigm shift in robotics, focuses on creating adaptable, flexible robots inspired by biological systems to engage safely and efficiently with intricate environments and living organisms. This study focus on the investigation of the performance characteristics of 3D-printed Soft Pneumatic Actuators (SPAs) fabricated from thermoplastic polyurethane using Fused Filament Fabrication. Through systematic experimental analysis, we evaluate how geometric parameters and operating conditions affect actuator behavior, specifically examining the relationships between the number of bellows (N), wall thickness (T), and operating pressure (P) on the resulting bending angle (α) and maximum force output (F). Tests were conducted on 45 actuator specimens, with bellows counts of 9, 11, and 13, wall thicknesses of 1.6, 2, and 2.4 mm, and operating pressures ranging from 1 to 3 bar. Results demonstrate approximately linear relationships between design parameters and actuator performance metrics. Increasing the operating pressure showed strong positive linear correlations with bending angle, while wall thickness demonstrated a strong negative linear correlation. For force output, operating pressure maintained a strong positive linear correlation, wall thickness showed a moderate negative linear correlation, while the number of bellows had only a weak positive correlation. Both bending angle and force output exhibited approximately linear relationships with these parameters, with deviations from linearity remaining fairly low across all configurations. The predictable, near-linear responses provide a robust foundation for performance-driven design optimization of SPAs for applications requiring precise control of movement and force generation.

Keywords: 3D printing , pneumatic actuator , precise control , soft actuator , soft material

Car seat comfort represents a fundamental dimension of automotive ergonomics, yet its assessment and optimization remain predominantly reliant on subjective feedback and iterative physical prototyping, limiting scalability and responsiveness in the design process. This study presents a novel data-driven framework that synergistically integrates statistical analysis and deep learning architectures enhanced with attention mechanisms to predict perceived driver discomfort from pressure distribution patterns. A comprehensive dataset acquired from 192 participants was used to extract biomechanical descriptors, such as contact area and peak pressure, across 9 anatomical regions, which were subsequently correlated with subjective discomfort ratings collected on a 10-point Likert scale. The proposed hybrid deep neural network achieved a modelling accuracy of R2 = 0.82 for overall discomfort, with peak pressure emerging as the most influential factor (Spearman's r = 0.78). Moreover, Finite Element Analysis (FEA) was employed to validate geometry refinements suggested by the AI model, resulting in an 18% reduction in peak seat pressure without compromising structural integrity. The findings underscore the transformative potential of integrating artificial intelligence with CAD–CAE methodologies to enable rapid, user-centered, and simulation-driven ergonomic design early in the vehicle development cycle, minimizing the need for physical prototypes and enhancing occupant comfort.

Keywords: AI-Driven Comfort Models , Deep Learning with Attention Mechanisms , Ergonomic Seat Design Optimization , Finite Element Validation of Human-Centric Design , Pressure Mapping and Biomechanical Analysis

Chewing simulators are essential tools in dentistry, as they enable the performance of innovative dental restorative materials to be analysed under realistic conditions. These devices replicate the complex movements and forces involved in mastication, enabling simulations of material wear and fatigue resistance. Their design and manufacture require a multidisciplinary approach that integrates mechanical engineering, materials science and dentistry, allowing the development of tools capable of improving the understanding of chewing processes and the effectiveness of dental treatments. This research focuses on a review of the main types of chewing articulators, highlighting the design and manufacturing aspects necessary to analyse the wear and the fatigue resistance of restorative materials. Construction characteristics, technologies employed and the most effective configurations for simulating realistic intra-oral conditions, including cyclic movements and variable forces, are highlighted. This study provides an overview of the main types of articulators currently in existence and their fabrication techniques, highlighting the importance of designing accurate, versatile, and increasingly reliable simulators. This allows to improve performance evaluation of dental materials while achieving greater success in patient-centred dental practices.

Keywords: Chewing articulators , Chewings' manufacture technique , Patient-centred treatment , Restorative material testing , Simulator design

The global demographic shift toward an aging population presents significant implications for automotive design and safety. This research addresses a critical gap in the literature by conducting a comprehensive ergonomic assessment of elderly drivers during two essential driving tasks: reverse gear maneuvers and seat belt engagement. Through a methodologically rigorous approach combining quantitative discomfort evaluations and postural analyses, this study examined a sample of 20 elderly people, a B-segment car and a strategically positioned recording equipment. The investigation revealed statistically significant patterns of discomfort concentration in the upper body regions, particularly the shoulders and cervical area, with Rapid Upper Limb Assessment (RULA) scores indicating substantial musculoskeletal risk factors. The findings demonstrate that conventional automotive configurations impose asymmetric postural stresses that are particularly problematic for elderly users due to age-related physiological changes. This research contributes to the theoretical understanding of aging-specific ergonomic requirements and provides empirical evidence supporting the necessity for adaptive design modifications to enhance safety, comfort, and continued mobility independence among the elderly population.

Keywords: Elderly population , Ergonomics , Postural Discomfort

Comfort is a pivotal construct in human-centered design, connecting technical functionality with well-being across products, services, and systems. The 2023 International Comfort Congress (ICC2023) brought together researchers and practitioners to explore how new contexts of use, predictive approaches, and user diversity are reshaping this field. Contributions in this special issue address comfort in automated driving and turboprop aviation, where physical, psychological, and environmental factors converge. Advances in predictive comfort science demonstrate how objective measures, physiological sensing, and modeling complement traditional self-reports. At the same time, inclusive design approaches—ranging from XR-based co-creation to analyses of posture and movement variability—highlight the importance of accounting for heterogeneous user needs and comfort trade-offs. Together, these studies illustrate a shift toward more adaptive, accessible, and sustainable systems, underscoring comfort as a multidimensional construct that evolves with technological innovation and societal change.

Keywords: accessibility , automated driving , comfort research , human-centered design , predictive modeling , user diversity

The EcoDAM (Eco-Design for Additive Manufacturing) project presents a comprehensive framework aimed at enhancing the environmental sustainability of metal additive manufacturing (AM) processes. Recognizing the complex interdependencies between material selection, manufacturing technologies, and lightweight design, the framework integrates four key steps: sustainable technology selection, lightweight design optimization, and a two-phase parametric life cycle assessment (LCA) involving both objective function formulation and constraint definition. Innovative methodologies such as function-oriented patent analysis, topological and lattice structure optimization, and parametric LCA modelling are employed to systematically evaluate and minimize environmental impacts throughout the AM product lifecycle. A case study based on Ti6Al4V connecting rod produced by laser powder bed fusion demonstrates the application of the framework, resulting in more than 50% weight reduction and improved sustainability performance. Key parameters, such as cell size and wall thickness of gyroid lattice structures, are optimized using finite element modelling simulations, while LCA constraints are formulated using experimental and literature-based data. The framework's modular design allows for industrial integration using commercial tools, enabling scalable, data-driven, and environmentally informed decision-making in AM. EcoDAM thus contributes a robust methodology for advancing circular economy goals in industrial AM.

Keywords: Additive manufacturing , Eco-design , Lightweight design , Parametric LCA , Patent analysis , Prospective LCA

This paper describes the design and preliminary testing of a soft exoskeleton for the shoulder which supports the adbuction/adduction movements. The soft exoskeleton is based on a single soft bellow actuator, a pneumatically actuated system which is composed by multiple consecutive chambers that expands when compressed air is inflated till providing a desired motion. In this work we present the design, analysis, prototyping and testing of the soft bellow actuator as well as its preliminary integration into a first version of bellow-based soft exoskeleton for the shoulder.

Keywords: Soft actuators , Soft exoskeletons , Soft robotics