Additive manufacturing

Hyper-redundant manipulators offer high dexterity and manoeuvrability in constrained environments, yet their design must integrate structural efficiency with environmental adaptability. This study presents a co-design framework for lightweight, cable-driven hyper-redundant manipulators optimised for underwater applications, such as the usage in combination with a Remotely Operated Vehicle. Building on a modular architecture of an eight-degree-of-freedom cable-driven manipulator, the methodology integrates Gaussian process regression-based stress prediction and generative design to achieve mass and size reductions, as well as a hydrodynamically efficient shape while ensuring structural integrity under extreme static loads. A 3D-printed module fabricated from Onyx, a carbon fibre-reinforced nylon, achieved near-neutral buoyancy in seawater, validated through submerged testing of a two-module prototype. An external buoyant element design was then provided for manipulators with no inherent buoyancy, accounting for printability, density mismatch between actual and theoretical density, and joint range of motion. This work advances underwater hyper-redundant robot design by combining data-driven optimisation with modular buoyancy strategies and hydrodynamic efficiency, providing a scalable method for fluid environments.

Keywords: Cable-driven , Design , Hyper-redundant , Manipulator , Optimisation , Robot , Underwater

In this paper, a Laser Powder Bed Fusion (LPBF) process is studied comparing the design of a Diesel piston with and without topological optimization. Starting from a commercial piston, an equivalent model and a topologically optimized one are designed, additively manufactured and post processed to set-up the starting framework to evaluate how Additive Manufacturing (AM) may impact the sustainability of an automotive product. Results highlighted a 27% mass reduction with a reduction of AM process duration of about 41% passing from a process lasted about 49 h for an AM piston with the original shape to about 29 h for 3D printing the topologically optimized one. Limits and further investigation are then discussed also in the perspective of a future assessment via LCA.

Keywords: Design for additive manufacturing , LCA , Lightweight design , LPBF , Topological optimization

Design for additive manufacturing is focusing on rules and methods to support new components development and redesign. In this paper, the design of a high-performance cryogenic silicon wafer holder is presented according to a design workflow able to accomplish the component redesign and optimization with and without lattice structure. The test case is a next-generation cryogenic detector for particle physics research, named BULLKID Project, applied in the field of neutrino and dark matter, and carried out by INFN (the Italian National Institute of Nuclear Physics) of Rome (Italy) with the support of Sapienza University of Rome (Italy). Starting from the design requirements that involve not only the performance but also assembly and manufacturing, a new silicon wafer holder is designed and manufactured by Laser-Powder Bed Fusion (L-PBF) with the aim of increasing the numbers of detectors per assembly. According to this development, via Computer Aided Engineering (CAE), the new design has been validated and printed. Redesign efficiency and drawbacks have been assessed with the perspective of the component lightweight also studying lattice insertion.

Keywords: Cryogenic applications , Design for additive manufacturing , L-PBF , Lattice structure , Lightweight design

This study presents the development of a prototype anthropomorphic soft robotic gripper intended for applications in rehabilitation and assistive robotics, where safe and adaptive interaction with humans is required. The device consists of three elastomeric fingers, fabricated in TPU via FFF 3D printing and actuated through pneumatic soft actuators that ensure compliant contact with both biological tissue and rigid objects. A custom 3D-printed pneumatic rotary actuator enables finger reconfiguration, thereby extending the range of grasping modalities. The actuation system comprises six 2/2 solenoid valves controlled by an Arduino Uno and integrated into a dedicated pneumatic circuit. Experimental characterization demonstrated a peak grasping force exceeding 17 N on rigid targets, while functional tests in table-picking scenarios confirmed adaptability to objects of varying shapes and sizes. Owing to its anthropomorphic configuration, mechanical compliance, and ease of fabrication and control, the proposed gripper represents a versatile solution for rehabilitation-oriented devices as well as assistive robotic end-effectors in pick-and-place tasks.

Keywords: additive manufacturing , assistive robotics , pneumatic , rehabilitation , soft actuator , soft gripper

Deploying deep neural networks on embedded systems is challenging due to stringent constraints on memory, compute, and power. DISTILLO (aDvanced Interactive ST knowledge distILLation) is a knowledge distillation framework tailored for classification tasks in resource-limited environments. It features two strategies: DISTILLO-Classical, using dynamic loss weighting with Kullback-Leibler or Jensen-Shannon divergence, and DISTILLO-Ensemble, which combines multiple student models distilled at different temperatures. Jensen-Shannon divergence is adopted to provide symmetric, bounded, and stable gradients, improving the robustness of the training. Experiments using Vision Transformers as teachers and lightweight CNNs as students show that DISTILLO-Classical achieves up to +5.37% accuracy gain on CIFAR-100 and +4.42% on Imagenette. DISTILLO-Ensemble further improves performance, reaching +13.97% and +8.32% gains, respectively, with minimal memory and latency overhead. DISTILLO enables the effective deployment of deep models on embedded platforms such as STM32 microcontrollers.

Keywords: embedded systems , knowledge distillation , low-resources

Eco-design for metal additive manufacturing (AM) can be pursued in different manners, including lightweight design and the reuse and recycling of powders. However, these options are contradictory due to the decline in characteristics in recycled and reused powders. This study proposes a parametric model of the environmental impact of AM process, including raw material extraction, metallurgical process, scrap recycling, melting, atomization for the production of the powders and printing. The model consists of an objective function that has been derived from the Life Cycle Assessment (LCA) methodology applied to the AM process. Each contribution of the function has been parameterized, including decision variables about mass reduction and the percentage of use of recycled and reused powder. The eco-design for AM is pursued through the minimization of the objective function (i.e., the environmental impact of the process) by obtaining the most suitable values of the decision variables. The proposed model has been applied to an illustrative example related to the AM of a component made by Ti6Al4V.

Keywords: Additive manufacturing , Eco-design , Parametric LCA , Parametric model , Recycled powders

This work presents a generative design algorithm for the semi-automatic reconstruction of sweepable surfaces from point clouds obtained through three-dimensional scanning. The proposed algorithm enables, starting from a 3D acquisition dataset, the correct automatic orientation of the mesh, the selection of a suitable cutting edge, and the specification of the number of transversal sections for an effective 3D model reconstruction. Additionally, it suggests a maximum number of points to be used for reconstructing the sectional curves. The mesh reconstruction is performed through a lofting operation, resulting in a non-uniform rational B-spline (NURBS) surface. The algorithm has been applied to a case study involving the front wing surface of a foil from the Olympic class iQFoil, which has recently garnered significant attention from researchers in the field of performance analysis. The obtained reconstructed surface exhibits very low deviation values when compared to the original mesh.

Keywords: 3D reconstruction , generative algorithm , innovative methods , iQFoil windsurfing foil

Metal binder jetting (MBJ) is an additive manufacturing technology of increasing interest due to its potential competitiveness in medium- and large-scale production, especially from a sustainability perspective. However, challenges in controlling the product accuracy and precision significantly limit the widespread adoption of this technology. This work investigates the achievable accuracy, precision, and spatial repeatability of parts produced using the MBJ process. Additionally, the paper aims to identify the causes of inaccuracy and suggest countermeasures to improve the product quality. The study was conducted experimentally by designing a benchmark geometry with various basic features. This geometry was scaled to three sizes—10–20 mm (small), 20–30 mm (intermediate), and 30–50 mm (large)—and produced using two different stainless-steel powders: AISI 316L and 17-4PH. In the green state, the dimensional tolerances ranged from IT8 to IT12 for features parallel to the build direction (heights) and from IT9 to IT13 for features parallel to the build plane (lengths). In the sintered state, the tolerances ranged from IT10 to IT16. This study reveals the challenges in scaling geometries to compensate for accuracy loss originating from the printing and sintering stages. In the green state, accuracy issues are likely due to non-uniform binder application and drying operations. In the sintered state, the accuracy loss is related to variable shrinkage based on the feature size, anisotropic shrinkage depending on the print direction, and differing densification mechanisms influenced by the material type. This study offers novel insights for improving MBJ process precision, supporting wider adoption in the manufacturing industry.

Keywords: additive manufacturing , dimensional accuracy and precision , metal binder jetting , shrinkage on sintering

Metal Binder Jetting (MBJ) is an additive manufacturing (AM) technology increasingly gaining interest due to its capability of producing complex products in medium-large batches, cost-effectively compared to other AM technologies. Nevertheless, dimensional accuracy is still challenging, also considering the significantly anisotropic shrinkage on sintering. The influence of printing parameters on the anisotropic shrinkage of two different geometries is studied in this work. Using fractional factorial Design of Experiments (DOE), four factors at three levels were considered (printhead speed, binder saturation, rake speed, and shell thickness). 30 cubes with squared through-hole, and 30 cylinders with circular through-hole were produced for each experiment using 316L; the shrinkage along different printing directions was derived from the dimensions measured at green and sintered state by Coordinate Measuring Machine. The optimal combination of printing parameters for the different geometries was identified using ANOVA. The effect of printing parameters on the two geometries was highlighted and discussed.

In recent years, Additive Manufacturing has experienced significant growth, yet its full potential is constrained by the lack of clear and easily replicable Design for Additive Manufacturing (DfAM) methodologies. Focusing on the product design stage, the current design approach for topology optimized parts involves an iterative re-design process to identify and reduce stress concentrations based on NURBS modelling, which is hardly replicable and heavily influenced by the designer's experience. This work aims to define two new workflows for DfAM that are easily replicable, highly automated, and based on numerical optimization tools. Leveraging the optimization tools available in 3DExperience integrated CAD platform, after topology optimization, the first workflow involves generating the skeletonization of the resulting geometry and reconstructing it with parametric surfaces, reducing maximum stresses via parametric optimization. The second workflow reconstructs the resulting optimized geometry as a non-parametric B-Rep surface, optimizing maximum stresses through automatic shape optimization.

Keywords: 3DExperience , Additive Manufacturing , Design for Additive Manufacturing , Design method , Design optimization , Parametric optimization , Shape optimization , Topology optimization

This study introduces a comprehensive life cycle model and tool to support the ecodesign of 3D printed components. The model, developed for Fused Deposition Modeling (FDM) technology, integrates both product and process-related parameters and encompasses all life cycle stages: (i) raw material production, (ii) part manufacturing, (iii) use, including application context and maintenance, (iv) end-of-life, and (v) transport. The model enables the predictive evaluation of environmental and economic performance through life cycle assessment (LCA) and life cycle costing (LCC), respectively, and using engineering design parameters as input. The FDM life cycle tool aims to guide decision-making during the early design phases by integrating sustainability metrics alongside conventional design requirements. It constitutes the kernel of a broader approach (called eDAM—ecodesign for Additive Manufacturing), which incorporates life cycle models, extensive data inventories, and technology-specific ecodesign guidelines. However, the development and implementation of the framework fall beyond the scope of the present study. The FDM model's applicability is demonstrated through a case study involving the production of a lightweight aerospace component (aircraft interior panel). The bio-inspired optimized 3D printed part exhibits notable reductions in greenhouse gas emissions and life cycle costs, confirming AM's potential for sustainability improvements in dynamic applications, including aeronautical systems. This tool outperforms other commercial tools used for environmental and cost assessment in additive manufacturing, in terms of built-in functionalities, product life cycle phases, and database breadth. The research highlights the scalability of the eDAM approach and its capacity to support engineers in achieving a balance between technical, economic, and environmental performance. Future work will extend the model to additional AM and conventional manufacturing technologies, refine specific life cycle phases (e.g., use-phase and end-of-life scenarios), and evaluate the usability and implementation efficiency of the model within the broader ecodesign framework.

Keywords: Additive manufacturing , Design for sustainability , Ecodesign , FDM , LCA , LCC , LCE , Life cycle assessment , Life cycle cost , Life cycle engineering

This study presents a scalable, nontoxic method for fabricating a 3D printable polycaprolactone (PCL)-collagen peptides composite filament via solvent-assisted blending and a customized desktop filament extrusion system. Virgin and recycled PCL feedstocks were used to study the matrix characteristics. Scanning electron microscopy, X-ray diffraction, differential scanning calorimetry, thermogravimetric analysis, and intrinsic fluorescence spectroscopy confirmed that the composite maintains PCL's inherent crystalline and thermal properties. It also exhibits intrinsic bioactive capabilities provided by the collagen peptides. Filaments with diameters suitable for the Fused Filament Fabrication 3D printing were obtained. Tests demonstrated that the recycled matrix and the lab-scale process reduce the tensile modulus of the material. At the same time, collagen peptides enhanced tensile stiffness by creating intermolecular hydrogen bonding with the PCL. The biocompatibility of the composite has also been confirmed, while degradability studies have shown the tunability of the PCL degradation rate. Additionally, examples of 3D-printed scaffolds based on Triply Periodic Minimal Surfaces have been successfully fabricated using the PCL-collagen peptide filament. Therefore, this study demonstrates that integrating collagen peptides into a PCL matrix represents a viable, nontoxic, affordable, and promising approach for developing customized and bioactive implants, scaffolds, and other regenerative medicine applications.

Keywords: 3D printing , Bioactive materials , Collagen peptides , Filament fabrication , Polycaprolactone , Tissue engineering

Background: – We aimed to describe a protocol and related surgical treatment for mentoplasty using virtual surgical planning (VSP) and piezosurgery. Methods: – Twelve patients requiring mentoplasty underwent VSP based on preoperative computed tomography. Virtual osteotomy was defined and the bone fragment was repositioned. Cutting and repositioning guides were exported as STL files and created using a 3-dimensional (3D) printer with biocompatible material. Plates were preblended on the printed model. Postoperatively, morphometric analysis was performed by comparing the planned and postoperative 3D models: distance between the apex of the cusp of 43 and 33 and lower edge of the chin; distance between the lower edge of the right and left mental foramen and osteotomy; and distance between the mandibular lingual fossa and pogonion. Results: – Six cutting guides were made composite and six were monobloc. The repositioning guides were all made monobloc. No adverse intraoperative events were observed. Postoperative transient hypoesthesia was reported in 1 case. The average distance between the planned and postoperative 3D models of the chin was recorded in translation (1.91 mm), rotation (right, 1.38 mm; left, 1.30 mm), and cranial-caudal repositioning (right, 1.39 mm; left, 1.23 mm). VSP and 3D printing have improved surgical precision and reproducibility; they help the surgeon decide the extent of chin movement and the most suitable type of surgical guide in advance. Conclusions: – Mentoplasty using 3D-printed guides and piezosurgery is simple, accurate, and safe. The costs of guide production are reduced using 3D printers by approximately €400–€800 per case compared with industrial printers.

Purpose – In Wire Arc Additive Manufacturing, the size and shape of the deposited material are affected by heat input, material deposition rate, orientation with respect to gravity, substrate conformation and the sequence of beads. The paper aims to investigate the geometric behavior of adjacent overlapping beads and proposes a model to predict the shape assumed in case of multiple beads deposition according to the succession of accumulation. Design/methodology/approach – Geometric curves such as parabolas, circular arcs, cosines and ellipses have been proposed in the literature to represent the resulting cross-section bead profiles, even though multiple beads deposition scenarios have been scarcely explored and, in most cases, restricted to simplified situations, such as planar substrates. Therefore, a generic geometric model for the bead profile based on a closed curve composed of two Hermite spans is proposed. Findings – The algorithm reliability was tested on circular specimens realized with a Fronius TPS 320i welding generator and on a set of documented cases from the literature. The results demonstrate that the Hermite curve-based model and the proposed algorithm can accurately reproduce various bead profiles in multi-bead and multi-layer deposition sequences. Originality/value – Thanks to the positioning of its control points, the Hermite curve exhibits the necessary variability in bead height, width, shape and contact angles with the substrate, offering greater flexibility in geometric approximation compared to existing models.

Keywords: Bead geometric modeling , Multi-bead deposition , Multi-layer deposition , Weld deposition , Wire arc additive manufacturing

Background: Intraosseous (IO) access is a life-saving procedure when intravenous access is impossible in pediatric emergencies. Proficiency in IO technique, particularly drill handling, patient positioning, and site identification, is essential to minimize complications and improve outcomes. Methods: To address the high cost and limited accessibility of commercial simulators, low-cost task trainers were developed using 3D printing and silicone casting. These trainers focused on drill handling, allowing trainees to progressively acquire procedural skills. Results: Initial validation was conducted with experts at Meyer Children's Hospital during a European Pediatric Immediate Life Support (EPILS) course. Structured feedback indicated high satisfaction with tactile realism and educational value. Based on this feedback, a second prototype with a fluid simulation system was implemented to enhance realism further. Nursing professionals, often first responders in emergencies, particularly benefited from the improved version, reporting increased confidence and competence. Conclusion: The cost-effective IO task trainers offer a scalable, realistic alternative to commercial models, expanding access to essential training. Their affordability and usability make them suitable for diverse healthcare settings, enhancing preparedness for pediatric emergencies.

Keywords: 3D printing , Clinical simulation , Intraosseous access , Nursing education , Pediatric emergency care

This study examines the influence of printing parameters and filament composition on the mechanical properties of 3D printed parts, building upon prior research in fused deposition modeling. Two combinations of printing parameters, 75% infill, 0° orientation, four outer shells, with either gyroid and 3D Honeycomb infill patterns—were analyzed across eleven materials, including acrylonitrile butadiene styrene, polylactic acid, polylactic acid-based composites, polyethylene terephthalate glycol, and high-impact polystyrene. Tensile, compression, and bending tests were performed on the printed specimens to determine stiffness and elastic modulus. Each material demonstrated different levels of variability and sensitivity to printing parameters under the various loading conditions, emphasizing that no single configuration is optimal across all scenarios. For example, the gyroid pattern led to increases up to ~35% in bending modules for common thermoplastic filaments and ~30% for stone-filled polymers, while in tensile stiffness, variations between infill patterns remained below 5% for other conventional polymers. These findings underline the load-specific nature of optimal parameter combinations and the influence of material-specific characteristics, such as filler content or microstructural homogeneity. This study provides quantitative insights that can support application-driven parameter selection in additive manufacturing, offering a comparative dataset across widely used and emerging filaments.

Keywords: 3D printing , composite filaments , FDM , mechanical properties , parameter optimization

Compliant mechanisms are systems that, using a single body, are able to perform functions typical of a traditional assembly with hinges, bars, and connecting parts. Since many structures in nature are designed in a logic of compliant mechanisms, it is reasonable to assume the enormous advantages, also in terms of sustainability, of this way of designing in engineering. To date, one of the main barriers to their diffusion is the lack of tools that can suggest the right topologies to the designer (pointers to geometrical effects), but also easy tools for their appropriate dimensioning and simulation. In contrast, additive manufacturing, thanks to its high compatibility with complex shapes and the recent ability to print multi-material parts, is bringing them back into the spotlight. The aim of this paper is to show the potential of DfC—Design for Compliant for the conception of more sustainable products, by presenting an exemplary case in which a comparison was made between the environmental impact of a traditional multi-part door lock made using standard manufacturing processes and a compliant system capable of replacing the former. To achieve even better results, the DfC-inspired concept was printed by multi-material additive manufacturing, using a combination of two different polymeric materials with very different Young's modulus to simulate different local behavior, both rigid and elastic. This substitution resulted in a reduction of CO2 equivalent impact around 50%.

Keywords: Design for compliant , LCA , Multi-material additive manufacturing

Additive technologies enable designers to conceptualize and produce components with local properties by manipulating their shape and material properties. In this sense, it is possible to create parts that exhibit heterogeneous or gradual properties variations in the volume. Among the numerous options to modify component properties, one can operate on the material itself. This is achieved by using materials that can change their final properties through the variation of process parameters. In fused filament fabrication, one strategy is to adopt a foaming agent with activation temperature suitable for the melting temperature of the material. In this work a design method for functionally graded properties components is developed for fused filament fabrication of materials with temperature activated foaming behavior. Two PLA materials are characterized with respect to their density, Shore D hardness, elastic modulus, ultimate tensile strength, elongation at break. Mathematical models for the characterized properties are subsequently derived to support the design phase. The design approach is based on a G-Code post processing routine which modifies the extrusion temperature and the material flow rate parameters.

Keywords: Design for additive manufacturing , Digital fabrication , Foaming , Functionally graded properties , Fused filament fabrication , Polylactic acid

In the recent years, the production of titanium powders has increased considerably due to the increase in uses, especially with additive manufacturing, in various application fields, including aeronautics and biomedical. Consequently, it is necessary to estimate the environmental sustainability of production processes while also considering the rapid technological evolution that characterizes them. This can be done with the prospective life cycle assessment (LCA) methodology, which estimates the future environmental impacts of an emerging technology or a new technology still in the R&D phase. This study generates prospective life cycle inventory (LCI) data of titanium powder production for additive manufacturing made with recent developments of Electrode Induction Gas Atomization (EIGA) reactors, which can be used in the prospective LCA. All data for the prospective LCI relating to argon consumption, water consumption, and electrical energy consumption of the EIGA reactor were extracted from the patents using a partly new approach. These data concern the experimental results (expressed through data ranges) obtained from laboratory-scale tests, qualitative and quantitative information to support the scale-up of the experimental data, and information to evaluate the data reliability.

Keywords: Additive manufacturing , Eco-design , Prospective LCA , Prospective LCI , Technological forecasting

Lattice structures are lightweight architected materials particularly suitable for aerospace and automotive applications due to their ability to combine mechanical strength with reduced mass. Among various topologies, Body-Centered Cubic (BCC) lattices are widely employed for their geometric regularity and favorable strength-to-weight ratio. Advances in Additive Manufacturing (AM) have enabled the precise and customizable fabrication of such complex architectures, reducing material waste and increasing design flexibility. This study investigates the low-velocity impact behavior of two polylactic acid (PLA)-based BCC lattice panels differing in strut diameter: BCC1.5 (1.5 mm) and BCC2 (2 mm). Experimental impact tests and finite element simulations were performed to evaluate their energy absorption ((Formula presented.)) capabilities. In addition to conventional global performance indices, a dimensionless parameter, (Formula presented.) is introduced to quantify the ratio between local plastic indentation and global displacement, allowing for a refined characterization of deformation modes and structural efficiency. Results show that BCC1.5 absorbs more energy than BCC2, despite the latter's higher stiffness. This suggests that thinner struts enhance energy dissipation under dynamic loading. Despite minor discrepancies, numerical simulations provide accurate estimations of (Formula presented.) and support the robustness of the (Formula presented.

Keywords: additive manufacturing , dimensionless index , drop-weight impact test , lattice structures , numerical and experimental comparison , PLA