Additive manufacturing

Structural topology optimization is a key method for designing lightweight and efficient components, particularly in additive manufacturing. In aerospace and automotive engineering applications, where components bear dynamic loads, it is crucial to account for natural frequencies and weight reduction. Traditional optimization methods often require labour-intensive manual setup, especially for tuning input parameters that influence the algorithm's performance and convergence. Machine learning offers an alternative, streamlining this process and reducing reliance on trial-and-error adjustments. This study introduces a machine learning-based framework to optimize input parameters—such as evolutionary rates and mesh dimensions—while ensuring the creation of lightweight, optimized structures with consistent natural frequencies. The framework uses a neural network trained on a dataset built to describe several configurations of a cantilever beam case study. The primary focus is determining the optimal dataset size for effective neural network training. The analysis aims to minimize dataset size, reducing the time and effort required for data preparation while avoiding overfitting in the neural network. A dissimilarity metric based on problem metadata is used to guide parameter tuning. After training, the artificial neural network is incorporated into the Bayesian Optimization framework as a surrogate model, enabling the new model to rapidly estimate outcomes without running full simulations. This approach substitutes traditional topology optimization algorithms, accelerates time-to-market, and is well-suited for applications with only minor variations in design conditions.

Keywords: Artificial neural network , Bidirectional evolutionary structural optimization (BESO) , Dataset analysis , Design for additive manufacturing , Frequency optimization , Topology optimization

Wire Arc Additive Manufacturing (WAAM) is a promising approach for the sustainable production of large-scale metal components. This study presents the first prospective Life Cycle Assessment (LCA) focused on the gate-to-gate manufacturing stage of seven patented, currently immature WAAM technologies. These technologies are projected to reach industrial maturity by 2035 and are evaluated in both laboratory-scale and anticipated industrial-scale configurations. Key findings reveal that future WAAM systems may reduce environmental impacts by an average of 45 % at the lab-scale and 74 % at the industrial scale compared to current WAAM. Argon shielding gas consistently contributes to more than 70 % of the total environmental impact. Plasma-based future WAAM significantly outperforms electric arc variants, exhibiting at least 20 % lower environmental impact than current WAAM systems. Multi-axis WAAM also demonstrates environmental advantages, with a 21 % lower impact compared to planar setups at the lab scale.

Keywords: Prospective LCA , Sustainable manufacturing , Technological forecasting , Wire Arc Additive Manufacturing

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

Conventional CAD tools face challenges with lattice structures due to the geometrical complexity and numerous facets of STL digital models typically used in additive manufacturing workflows, prompting the need for alternative methods. This paper introduces a function representation-based approach to model uniform lattice structures using a 1D wireframe model followed by surface triangulation. The study highlights the efficiency of generating lattice structures using this method compared to other techniques available in the literature and traditional boundary representation. Unlike traditional methods, this approach removes the necessity for boundary representations of lattice structure models, resulting in more efficient data management. The findings of this research have significant implications for the development of lightweight 3D components optimized for additive manufacturing and their representation in CADs. This method is designed for industrial applications where rapid and efficient design of complex geometries is essential for achieving lightweight components.

Keywords: CAD modeling , Function Representation , Lattice structures , STL Triangulation

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

The purpose of this paper is to evaluate the evolution of sustainability research in Additive Manufacturing (AM) by providing an overview of systematic literature reviews (SLRs) published between 2016 and early 2025. Nine SLRs were selected following the screening and filtering of 204 records identified through a structured search of the Scopus database. The following criteria were used to analyze and compare these articles: (i) their scope, (ii) data sources of literature considered, (iii) sustainability dimensions covered, and (iv) the main findings and key conclusions (e.g., significant patterns, recurrent themes, methodological advancements). The study highlights that AM is widely recognized as a transformative technology capable of fostering more sustainable, localized, and resilient production systems. However, realizing its full sustainability potential requires further research, methodological standardization, integration of lifecycle thinking, digitalization, and greater attention to social dimensions. Although AM demonstrates clear economic advantages, the social pillar of sustainability remains underexplored, with limited research addressing concerns such as occupational health risks and the demand for skilled labor in emerging economies.

Keywords: Additive manufacturing , Meta-review , Sustainability

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

Soft end-effectors that can pick delicate produce without bruising are pivotal for agricultural robotics yet remain hampered by limited load capacity and uneven force sharing. We present HSA-TriGrip, a lightweight three-finger gripper whose fingers each combine two handed shearing auxetic (HSA) modules in a gear-coupled arrangement. A single motor drives all fingers via one fishing line tendon; local slip inside the finger connectors yields a passive differential that equalizes travel and grip force. Thin-film force sensors are integrated on the inner phalanges to measure gripping pressure. The 715 g prototype—of which the distal gripper accounts for only 21 %—maintains an aggregate grip of ≈130 N after a 40-cycle run-in and endures 100 fatigue cycles at 96 % of its initial capacity. With tendon slip enabled, pull-out resistance reaches 168 N (29 % above the locked mode) and all three fingers engage. These results confirm that coupling auxetic actuation with passive tendon differentials delivers a self-balancing, bruise-mitigating grasp suited to field harvesting.

Keywords: Cable-Driven , Handed-Shearing-Auxetic Actuator , Soft Harvesting Gripper , Underactuation

Lattice structure design is still dominated by strut-based forms and surface-based shapes, such as triply periodic minimal surfaces (TPMS), which both exhibit overlapping limitations. Strut lattices often show strong anisotropy because theirresponse depends heavily on cell orientation, while TPMS lattices are difficult to adjust when bounded by geometric constraints. These conditions eventually led to stagnation in the development of lattice morphology. Hybrid and topology optimization methods have appeared as possible alternatives, but many of them still produce modified versions of classical patterns. This study examined two lattice geometries: the Pyramorph, inspired by the shape of a pyramid, and the Topomorph, generated through a topology optimization framework. Both structures were designed using a CAD unit cell patterning technique and manufactured using the FDM method, with relative densities ranging from 0.40 to 0.44. Their mechanical behaviour was examined through FEA simulation and uniaxial compression testing. The parameter variations included cell orientations of 0°, 15°, 30°, and 45°, and cell sizes of 8 mm and 12 mm within a 24 mm specimen. The Topomorph showed superior strength, reaching 15–20 MPa, while the Pyramorph reached only 7–8 MPa. The highest value, about 20.5 MPa, was obtained from the Topomorph at 0° and with an 8 mm cell size. Failure modes indicated buckling and delamination in the Pyramorph, while the Topomorph tended to collapse progressively. These findings indicate that topology optimization combined with CAD-based patterning could significantly improve lattice performance.

Keywords: compressive behaviour , lattice structures , material engineering , topology optimization

Additive Manufacturing (AM) displays unique capabilities in terms of fabricating parts including unconventional geometries. Much research is conducted to investigate the performances of AM from both the mechanical and the quality viewpoint. This research is aimed to complete the transition of AM from a rapid prototyping technology to a mature manufacturing option. Interestingly, this research is routinely conducted on standard geometries instead of those kind of topologies for which AM is an advantageous fabrication system. The study presented here originally compares the accuracy of AM for standard and complex shapes. As a case study, we used the model of a leg of a quadruped robot obtained with generative design in previous research. The model includes standard and non-standard geometries, with the latter being predominant. Ten copies of this model have been produced by AM, specifically by means of a 3D printer working with Fused Deposition Modelling. Two different orientations have been used for the model (five copies each). The 3D-printed physical models have been 3D-scanned and compared with the reference CAD model, which has allowed us to evidence deviations. The deviations have been displayed by using both global and local best-fit options in a quality assessment software application. The first analysis of achieved data suggests that printing parameters and the position of surfaces affect the accuracy of AM more than the characterization of surfaces as standard and non-standard.

Keywords: Additive Manufacturing , Deviations , freeform , Generative Design

3D printing is transforming the construction industry by reducing material waste, enhancing design flexibility, and shortening construction timelines. As a rapidly advancing technology, it offers innovative solutions for efficient, sustainable, and advanced building practices. This study aims to give an overview of the contents treated in the literature on 3D printing of concrete, with a focus on key topics, technologies, applications, and parameters influencing printability. Following a systematic review process, 1079 studies were analyzed in terms of objectives, structural applications, and printing technologies. The findings reveal a strong emphasis on parameters such as strength, interlayer bonding, and rheological properties, while durability-related aspects like freeze-thaw resistance and water absorption are explored more seldom. The study underscores the need for material optimization to balance fresh-state and hardened-state properties, ensure long-term structural performance, and incorporate sustainable materials. By addressing these gaps, this research identifies critical pathways for advancing 3D printing in construction and provides recommendations for achieving durable, efficient, and environmentally sustainable solutions.

Keywords: 3D Printing , additive manufacturing , construction sector , structural applications

The recent increase in environmental challenges and concerns has enhanced global awareness, forcing a shift towards sustainable manufacturing to improve resource efficiency and reduce waste generation. Additive Manufacturing (AM) is considered sustainable, albeit in different ways depending on context and products. This study aims to shed light on AM adoption, highlighting how experts perceive the sustainability of AM, and this affects the selection of AM for part fabrication. A semi-structured interview revealed that experts have diverse perspectives on using AM, recommending or rejecting it for producing specific parts and identifying distinct sustainability hotspots. The hotspots classified under process sustainability were the most critical factors in process selection, followed by those about corporate and part (i.e., structure and geometry) sustainability. Overall, reducing the mass of raw material, reducing production time, part customizability, and surface quality resulted as the most mentioned factors within manufacturing process selection. Overall, AM was found to be more suitable than traditional manufacturing for process sustainability primarily due to time and cost, corporate sustainability for product customizability, and less for part sustainability due to poor finishing.

Keywords: Additive manufacturing , Decision-making , Environmental hotspots , Expert , Semi-structured interview , Sustainability

3D printing offers transformative potential in construction, yet optimising the performance of cementitious materials before and after extrusion remains a critical challenge. This study presents a performance-based mix design framework targeting extrudability, buildability, and layer stability, while evaluating the individual and combined effects of cement (C), hydrated lime (L), recycled tile powder (T), and chemical accelerators (A). Results reveal that their synergy significantly enhances rheology, yield stress, and print stability, while maintaining sufficient flowability. A specifically optimised mix, CLTA, achieved a 40% reduction in shrinkage, improved interlayer bonding, and markedly increased mechanical strength, modulus of toughness, and failure strain, key for energy absorption in printed structures. Environmentally, CLTA reduced raw material demand and improved eco-strength and cost-efficiency by up to 20%, promoting circularity and resource efficiency. The findings provide a robust pathway for designing high-performance, sustainable 3D-printed mortars, integrating engineering functionality with ecological resilience, paving the way for broader adoption of additive manufacturing in construction.

Keywords: 3D printing , cementitious mixtures , mechanical properties , printability , sustainability , viscosity

Featured Application: The methodology presented in this work enables the direct extrusion-based 3D printing of soft, low-hardness RTV-2 silicone elastomers using industrial additive manufacturing systems. By adapting commercially available general-purpose silicones through viscosity tuning, the proposed approach expands the material palette for silicone additive manufacturing beyond proprietary formulations. This capability is particularly relevant for applications requiring highly compliant, biocompatible, and geometrically complex parts, such as soft robotics components, customized prosthetic and orthotic devices, medical simulation models, wearable interfaces, and flexible seals or gaskets. A particularly relevant industrial scenario for the proposed methodology is the small- to medium-batch production of customized silicone components, where traditional mold-based casting becomes economically inefficient due to tooling costs and long lead times. This study investigates the relationship between viscosity and manufacturability of two-component silicones in extrusion-based additive manufacturing. A methodology is proposed to adapt commercially available, low-viscosity general-purpose silicones for direct 3D printing using the material extrusion system provided by Lynxter S300X. EcoFlex™ 00-50 silicone was modified through controlled additions of a thixotropic agent (THI-VEX), producing formulations with progressively increased viscosity. After a preliminary qualitative viscosity assessment, formulations were printed using identical process parameters and evaluated through a set of dedicated geometric benchmark specimens targeting critical failure modes, including unsupported thin walls, overhangs, gaps, and slender structures. Print outcomes were assessed via multi-rater visual inspection with inter-rater reliability analysis to ensure consistency. Results reveal a strong correlation between thixotropy and geometric fidelity, identifying the formulation containing 4.0 wt% THI-VEX as optimal under the tested conditions. The study provides practical design and process guidelines for silicone additive manufacturing and highlights the importance of integrated material–process optimization for reliable fabrication of soft, highly deformable materials.

Keywords: geometric printability , material extrusion , RTV-2 silicone elastomers

Wrist impairments are common in post-stroke and elderly populations, often requiring rehabilitation to restore joint mobility and strength. However, clinic-based programs pose accessibility challenges, especially for patients with limited mobility. This paper presents W.R.I.S.T. (Wrist Rehabilitation Intelligent Support Tool), a soft robotic prototype designed to facilitate wrist flexion-extension exercises in home settings. The system features an inflatable silicone handle integrated into a 3D-printed structure, equipped with a flexion sensor for monitoring and a pneumatic circuit for real-time resistance modulation. A microcontroller manages pressure regulation and sensor data acquisition, enabling adaptive therapies and personalized training. Experimental validation confirmed a predominantly linear relationship (R2 > 0.85) between sensor output and flexion angle across pressure levels, ensuring reliable motion tracking. Additionally, a game-based interface was developed to enhance user engagement, transforming repetitive exercises into an interactive task with customizable difficulty. The integration of adjustable mechanical resistance and interactive feedback supports progressive rehabilitation while promoting adherence. W.R.I.S.T. offers an affordable, customizable, and valid solution for decentralized rehabilitation, particularly suitable for elderly users or those with limited access to clinical services.

Keywords: 3D printing , Pneumatic , Rehabilitation , Soft Material , Wrist

Piezoelectric material extrusion is a novel material extrusion technique that deposits thermoplastic materials in droplets, by means of a piezoelectric nozzle regulating the material flow. This improves the performance of the machine, with respect to Fused Filament Fabrication, by enabling higher precision in material placement and better control over deposition volume. A common limitation of this technology lies in the fabrication of overhanging structures, where precise droplet deposition is inherently more complex and prone to inaccuracy. The research investigates the impact of a key process parameter, specifically Droplet Aspect Ratio, on the dimensional accuracy of printed specimens and on the quality of overhang surfaces. The research considers bridging and the prioritization of infills in the deposition strategy as additional variables. An experiment based on the fabrication of 50 specimens, optimized for overhang quality evaluation, was performed. Specimens were analysed through 3D scanning techniques. The study demonstrates a strong correlation between Droplet Aspect Ratio and the dimensional accuracy of overhanging surfaces. The integration of bridging structures significantly improved surface quality by providing additional support, with the greatest benefits observed at 27° inclination. Prioritizing infill deposition before outer contours resulted in a marked reduction in defect levels at high DAR values.

Keywords: additive manufacturing , droplet aspect ratio , overhang , pellet-based material extrusion , piezoelectric nozzle

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

Viscoelastic polymers are increasingly employed in lattice structures for their absorption and damping capabilities, particularly in applications involving vibration suppression or impacts. These structures exhibit remarkable properties, such as high specific stiffness, specific strength and energy absorption capacity, making them highly attractive for applications in aerospace, automotive, and biomedical fields. However, the accurate modeling by taking into account frequency-dependent behavior, especially for applications involving damping, remains challenging due to the interplay between geometric complexity and material viscoelasticity. To address this challenge, this study makes use of a general numerical homogenisation method enhanced for frequency-dependent material properties in order to predict the damping of the lattice structure at the macroscopic scale. A fractional derivative constitutive model is used to describe the frequency-depend behaviour of the bulk material, while a custom Ansys APDL code is developed to adapt the homogenisation method to the case of material with frequency-dependent properties. The results demonstrate that, for lattice structures made of a single material phase, it is possible to perform the homogenisation process at an arbitrary frequency. The resulting stiffness tensor of the equivalent homogeneous anisotropic material that replaces the structure at the macroscopic scale varies with frequency according to the same law used for the bulk material at a lower scale. Furthermore, the results show that even if the stiffness tensor of the lattice structure at the upper scale exhibits elastic symmetry depending on the topology of the unit cell, the damping matrix at the upper scale is unaffected by the lattice topology.

Keywords: Homogeneization , Lattice structures

Mandibular and maxillary bone regeneration is a significant challenge in orthodontics and maxillofacial surgery, particularly in patients with bone atrophy or advanced periodontal diseases. This study presents an innovative approach that integrates advanced imaging and manufacturing technologies to design and fabricate customized scaffolds based on data obtained through Cone Beam Computed Tomography (CBCT). The objective is to create biomimetic bone scaffolds suitable for infusion with autologous stem cells, promoting functional bone regeneration. The workflow comprises three key stages. CBCT images are processed to reconstruct detailed three-dimensional models of the mandibular or maxillary structure. Then, using generative optimization algorithms and surface subroutines in commercial CAD software, scaffolds are designed to replicate the mechanical, geometric, and biological properties of natural bone. The scaffolds are fabricated using 3D printing techniques with biocompatible and biodegradable materials. 3D printing enables high precision in creating porous structures optimized for vascularization, cellular integration, and mechanical support. This multidisciplinary approach, combining medical imaging, CAD/CAM design, and additive manufacturing, offers an advanced solution to address the challenges of bone regeneration in orthodontics. Preliminary results suggest that infusing scaffolds with stem cells could significantly accelerate bone regeneration and improve integration with surrounding tissues. Future studies will focus on preclinical validation of scaffolds.

Keywords: Biocompatible material , Biodegradable material , Bone scaffold , DICOM images , Mandibular and Maxillary Reconstruction