Additive manufacturing

The present study introduces a novel approach for pattern recognition to analyze the surface hardness of metal parts made by 3D selective laser melting (SLM). A printed part's hardness is further influenced by post-processing, printing parameters, and post-print material handling. Layer by layer, material is deposited in 3D printing, sometimes referred to as additive manufacturing, to turn a digital design into a tangible product. More complex and adaptable designs are possible because 3D printing adds material rather than removes it, in contrast to conventional manufacturing techniques (such as machining or molding). The current work models the surface hardness of 3D selective laser melting of metal materials using genetic programming and network theory. To assess the hardness of 3D selective laser melting of metal materials, we introduce a novel pattern recognition technique. We apply fractal geometry analysis to determine the complexity of 3D selective laser melting of metal materials.

Keywords: Additive manufacturing , Fractal geometry , Genetic programming , Network theory , Selective laser melting , Surface hardness

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

Liquid Crystal Elastomers combine the elasticity of polymer networks with the anisotropic ordering of liquid crystals, thus enabling reversible shape modifications and stimulus responsive actuation. Unfortunately, manual LCE fabrication remains limited by operator-dependent variability, which can lead to inconsistent film thickness and manufacturing times inadequate for a mass production. This work presents a low-cost, automated manufacturing framework that redesigns the mechanical assembly steps of the traditional one-step LCE fabrication process. The design includes rubbing, slide alignment, spacer placement, and infiltration cell assembly to ensure consistent film quality and scalability. A customized Cartesian robot, built by adapting a modified X–Y core 3D printer, integrates specially designed manipulator systems, redesigned magnetic slide holders, automated rubbing tools, and supporting fixtures to assemble infiltration devices in an automated way. Validation tests demonstrate reproducible infiltration, improved mesogen alignment confirmed via polarized optical microscopy, and high geometric repeatability, although glass-slide thickness variability remains a significant contributor to deviations in final film thickness. By enabling parallelizable low-cost production, the designed hardware demonstrates its effectiveness in devising the scalable manufacturing of LCE films suited for advanced therapeutic and engineering applications.

Keywords: automated manufacturing , cartesian robotics , liquid crystal elastomers (LCEs) , mesogen alignment

Objective: Pediatric airway management presents unique challenges, particularly in patients with congenital conditions that increase the risk of difficult intubation. Simulation offers a safe environment for clinicians to practice, yet current pediatric mannequins often lack pathological realism. This study aims to develop and validate a high-fidelity, patient-specific pediatric airway mannequin simulating difficult intubation associated with Crouzon syndrome. Technology or Method: A modular training mannequin was developed through CT-based modeling and additive manufacturing at the T3Ddy Laboratory, a collaboration between AOU Meyer Children's Hospital-IRCCS and the University of Florence. Anatomical structures were segmented from CT and MRI scans of a 19-month-old patient with Crouzon syndrome. These 3-D models guided the design of a realistic airway, including nasal and oral access, a flexible tongue, and a movable jaw. Rigid parts were 3-D-printed; soft tissues were cast in silicones of varying hardness. Design choices were validated through iterative testing and refinement. Results: The simulator was evaluated during a pediatric bronchoscopy training course. Physicians assessed realism, tactile feedback, and usability via a Likert-scale questionnaire. Results indicated strong agreement on the mannequin's effectiveness in replicating challenging intubation scenarios, particularly those requiring fiberoptic-guided techniques. Conclusion: This modular, patient-specific pediatric airway simulator provides a realistic, high-fidelity platform for training clinicians in difficult intubation techniques. Its anatomically accurate design enhances procedural confidence and skill acquisition, particularly for managing complex cases like those associated with Crouzon syndrome.

Keywords: 3-D printing , additive manufacturing , Crouzon syndrome simulator , pathological airway , pediatric simulation

The droop-nose leading-edge morphing wing offers promising potential for reducing aerodynamic drag and noise during take-off and landing, thereby helping to lower aircraft fuel consumption and align with greener aviation goals outlined in Flightpath 2050 by the EU and ICAO declarations. Despite technological challenges and current technology readiness levels (TRL), droop-nose leading-edge (DNLE) wings are primarily tested and evaluated in unmanned aerial systems to reduce costs and risks. The literature proposes various optimisation methods for airfoil skin and morphing mechanisms; however, additional research contributions are needed to develop an effective design methodology. High actuator forces required for morphing, the trade-off between skin flexibility and load-bearing capacity, and the difficulty of obtaining smooth and continuous airfoil deformations are still under investigation. The present research introduces an optimisation methodology tailored for DNLE composite laminate skin and morphing mechanism structures. Its application to the UAS-S45 unmanned vehicle is utilised as a case study. Applying this design and optimisation methodology can lead to an 88% reduction in actuator mechanism force for a DNLE optimised for 6° angle-of-attack, considering an airfoil. This approach significantly enhances airfoil shape smoothness across sections and spanwise direction during morphing conditions. The proposed approach reduces the computational effort, as non-linear finite element method (FEM) analyses are not required within the optimisation loop, except at selected verification stages. A mechanism prototype was constructed to validate the FEM analyses and understand the limits of the simulation. Further investigations are required to achieve a morphing shape closer to aerodynamically optimised shapes.

Keywords: aeronautical design , composite materials , morphing airfoil , structural optimisation

Additive manufacturing technologies enable the realization of complex and free-form geometries that are difficult or impossible to realize with traditional subtractive processes. The development and widespread use of algorithmic optimization methods, including topology and shape optimization, lattice structures, and generative design, accelerate this manufacturing revolution. The redesign of existing parts is a common practice to improve the overall performance of mechanical systems. The practice of designing additive manufacturing components, known as Design for Additive Manufacturing, enables designers to enhance functionality, reduce the number of parts, and minimize the overall weight, thereby obtaining an optimized shape for the analyzed item. This paper proposes a method to support designers in applying optimization techniques for mechanical components. The paper also applies the proposed approach to redesign an automotive suspension arm for a C-segment passenger car. The case study begins with the analysis of a reference part produced using conventional manufacturing and ends with the proposal of a new geometry to be realized by metal 3D printing.

Keywords: Design for Additive Manufacturing , Design Optimization , Shape Optimization , Suspension arm , Topology Optimization

This explorative study investigates the integration of artificial intelligence (AI) and composite-based additive manufacturing (AM) in the design and fabrication of yacht components. Traditional manufacturing methods in the nautical sector impose significant constraints on customization and sustainability. By leveraging AI-powered text-to-3D tools and fused deposition modelling (FDM) with carbon fiber-reinforced polymers, this work demonstrates the feasibility of generating and manufacturing structurally simple yet functionally relevant yacht components. The design pipeline involved iterative prompt engineering, AI-assisted 3D model generation, and physical prototyping. Model generation required multiple attempts and human-in-the-loop selection to achieve functional realism and printability. The printed parts exhibited overall good visual and structural quality, indicating a promising pathway for fast, sustainable prototyping. Although limited to three relatively simple case studies, the results validate the potential of AI-AM workflows to overcome traditional manufacturing constraints. Future developments will focus on expanding components complexity and dimension, incorporating mechanical testing to assess structural viability, and refining AI-generated geometries for improved functional fidelity. This study supports a paradigm shift in yacht design, highlighting AI and AM as enablers of flexible, efficient, and sustainable product innovation.

Keywords: Additive Manufacturing , Artificial Intelligence , Composite Materials , Fused Deposition Modelling , Yacht Design

Additive Manufacturing (AM) is no longer limited to prototyping, as it is gaining an increasingly large market share. With this expansion, there is a growing demand for the development of standardized rules to establish product specifications and verification procedures. AM offers unique opportunities in free-form shape design and multi-material processing, in contrast to traditional manufacturing processes and communication methods. Because of AM's unique features, existing standards struggle to describe its product specifications. New regulations are therefore under development This paper reviews the state of the art in Additive Manufacturing (AM) product specification. This research examines the most up-to-date literature and standards published by the ISO, and ASME committees. A research gap has been identified in the accurate determination of design intent, which is crucial for defining product specifications. “Profile tolerance” is recognized as the most versatile specification for free-form geometries; however, new tools can be developed to control lattice structures. Additionally, the authors identified a significant gap in the assessment of dimensional and geometrical deviations in AM processes, as these are often estimated using geometrical benchmarks designed for subtractive technologies. Finally, verification remains one of the most critical aspects of AM products. Computed Tomography (CT) currently represents the only viable approach for measuring inaccessible features; however, standardized reconstruction methods are still lacking, as is a specification method tailored specifically for this measurement technique.

Keywords: Additive Manufacturing , DfAM , Dimensional and Geometrical Specification , Product Specification

This study investigates the dimensional change on sintering of products printed via the binder jetting (BJ) additive manufacturing (AM) process, using a powder mixture of stainless steel 316 L and 1 wt% red mud. This research is a part of a vast project aiming to develop continuous-feeding anodes for direct carbon fuel cells (DCFC). Cubes with a through-hole were printed to assess dimensional change during sintering. The geometries of the samples were carefully reconstructed before and after sintering using points acquired by a coordinate measuring machine (CMM). The results reveal a slightly lower shrinkage of the powder mix compared to the reference 316 L material. Novel scaling factors have been proposed to compensate for dimensional changes in future anode production. Additionally, the shape of the cubes was highly distorted after sintering, especially along the powder spreading direction. Finite element simulations reveal the impact of the density gradient in the green state on the origin of sintering deformation. This density gradient, estimated at approximately 0.5% of the relative density per millimeter, is likely caused by the poor flowability of the powder mix.

Keywords: Binder Jetting , Composite Material , Density Gradient , Dimensional Accuracy , Red Mud , Sintering Simulation

The growing need for sustainable mobility is driving the search for solutions to reduce energy waste and harmful environmental emissions. In this context, the design of vehicle lighting presents a promising approach. The use of composite materials, along with the automation of their manufacturing and assembly processes, is increasingly in demand to strike a balance between cost, lightweight, and the required performance of vehicle chassis. Carbon Fiber Sheet Molding Compounds allow complex car body parts to be produced through a one-step compression molding process. Manual labor represents a crucial operation in preparing the compound charge and subsequent manipulation towards compression molding. However, it directly affects productivity. The continuity between the preparation and manipulation phases can be relaxed by implementing robotic solutions to handle the pre-shaped uncured composite charge, automating loading onto the press mold. Efficient robotic handling requires grippers designed to match the shape of the compound charge. Specifically, the gripper must control the deformation of the temporary form of the composite charges, ensuring that the shape deviations stay within acceptable limits for proper fit in the compression mold. This work presents a systematic approach to designing and optimizing robotic grippers to pick up and place deformable compound layers. The key design parameter that guides this method is the maximum distortion threshold, which regulates the process in the two stages. The first stage focuses on finding the optimal balance between the lowest grasping points and acceptable distortion to define the grasping layout. In contrast, the second stage addresses the gripper structure, aiming to create the lightest, yet stiffest frame. The approach is fully integrated into a computer-assisted design platform.

Keywords: CF-SMC , Integrated design , Limp uncured composite geometries , PLM Platform , Robotic Grippers

Directed Energy Deposition (DED) is increasingly utilized for the construction of large components, repair of worn and damaged parts, and integration into Hybrid Manufacturing systems to leverage diverse technological features. A burgeoning application of DED is in Additive Remanufacturing (ARem), by which existing components can be enhanced with additional features and materials to improve functionalities. This paper presents a systematic and integrated approach for Design for Additive Remanufacturing (DARem), focusing on the optimization of product structural requirements to enhance performance and the process design to minimize flaws while ensuring material integrity and expected tolerances. The suggested approach involves product and process design phases within a computer aided design platform. Identification of critical issues in the original product design is the fundamental phase that drives the selection of the appropriate materials and quantities for deposition. Next, topological optimization is employed to shape and position additional volumes, generating enhanced design variants. A simulation phase ends the product design steps, assessing the actual improvement of the component over its original design. Subsequent phases are related to process design assessment. Selection of process parameters and build strategies, and next, the behavioral simulation of deposition are fundamental to verify feasibility and generate paths instructions. Finally, thermomechanical simulation is conducted to estimate the final component state accurately, ensuring it meets functional requirements before proceeding to actual manufacturing pre-processing, material deposition, and post-processing phases. A case study involving an automotive suspension component is used to demonstrate the feasibility of the proposed integrated approach. Experimental phases are performed to define DED material properties for the redesign and investigate the reliable simulation of process-induced distortions. By reducing stress in critical areas through localized deposition of 316L stainless steel alloy using laser powder DED, the study explores the impact of toolpath strategies on process-induced distortions through a Design of Experiments (DoE) approach. The results confirm the feasibility of the deposition process in meeting functional requirements, particularly geometrical tolerances, highlighting the potential of DARem for the redesign and enhancement of existing components.

Keywords: 316L, Remanufacturing , Directed Energy Deposition , Finite Element Method , Product-Process design

This study concerns the analysis of lattice structures printed with EPAX resin for the manufacturing of a motorcycling throttle cam with Response Surface Methodology (RSM) and Artificial Neural Networks (ANNs). The design of the pattern core in the lattice structure is defined parametrically to identify optimal design points (best stiffness to weight ratio in particular). Some geometric parameters used as input in RSM and in the NN analysis include the origin of the lattice structure and its spatial orientation, cell dimensions, and thicknesses. The dataset obtained with this approach is used for an RSM analysis of variance (ANOVA) to highlight the most important inputs. NN analysis is performed on the same RSM dataset to confirm the results. Both methodologies identify in-domain points of optimal design due to the typical non-linear behavior of these structures. The literature and industrial experience already provide numerous references to studies characterizing lattice structures. However, related practical applications are often incomplete and only achieve functional rather than optimal models. The approach described also aims to overcome this limitation. The software used for the design is nTop 5.0.4.

Keywords: artificial neural networks , lattice structures , resin additive manufacturing , response surface method , stiffness optimization

(1) Background: HTPLA FDM-printed cutting guides enable the low-cost, in-hospital production of patient-specific instruments. However, annealing, which is required for steam sterilization, may alter the dimensions of fit-critical fixation pin holes. (2) Methods: HTPLA cylindrical specimens (height 5 mm) were printed with fixed process parameters and vertical orientation. Inner diameter (1.6–5.0 mm) and wall thickness (2–6 mm) were varied using a two-factor Central Composite Design (n = 13). Following a two-stage annealing treatment (80 °C, 10 min; 100 °C, 50 min), post-annealing dimensions were measured and modeled using Response Surface Methodology. An illustrative verification was performed on additional specimens. (3) Results: Annealing induced a systematic decrease in inner diameter (−0.4 to −0.9 mm) and an increase in wall thickness (+0.1 to +0.4 mm). A reduced quadratic model accurately captured these trends within the investigated range, with small residuals observed during verification (≤0.1 mm). (4) Conclusions: The proposed local, geometry-driven model supports compensation in fixation pin-hole dimensions in annealed HTPLA cutting guides, improving dimensional predictability within a defined design and process window.

Keywords: 3D printing , annealing , cutting guides , deformation , fused deposition modelling , high-temperature polylactic acid , orthopedics , PLA , polylactic acid , thermal treatment

This study aims to gather a sustainable understanding of additive manufacturing and other Manufacturing 4.0 approaches like horizontal and vertical integration and cloud computing techniques with a focus on industrial applications. The DfAM will apply 4.0 tools to gather product feasibility and execution, with CAE—FEM analysis and CAM. This publication focuses on the redesign of a vehicle suspension arm. The main objective is to apply innovative design techniques that optimize component performance while minimizing cost and time. The IDeS method and TRIZ methodology were used, resulting in a composite element, aiming to make the FDM-sourced process a viable option, with a weight reduction of more than 80%, with less material consumption and, hence, less vehicle energy consumption. The part obtained is holistically sustainable as it was obtained by reducing the overall labor used and material/scrap generated, and the IDES data sharing minimized rework and optimized the overall production time.

Keywords: additive manufacturing , IDeS , product design , product reverse engineering , TRIZ

The increasing demand for lightweight materials with high mechanical performance has accelerated the development of hybrid composite-metal joints, especially in the transportation industry. Despite their advantages, these joints often present challenges in terms of manufacturability, reliability, and environmental impact. This study evaluates the environmental performance of composite/metal hybrid joints by comparing two scenarios: with and without penetrative reinforcements produced by Additive Manufacturing (AM). A Life Cycle Assessment (LCA) was conducted in accordance with ISO 14040:2021 and ISO 14044:2021 standards, adopting a cradle-to-gate approach. The functional unit was defined to ensure comparability across both scenarios. Primary data were obtained from experimental setups, while secondary data were sourced from scientific databases such as Ecoinvent. Results indicate that the introduction of AM-based reinforcements leads to an 80% increase in tensile strength, enabling a significant reduction in bonding area. This geometric optimization results in a notable decrease in the environmental burden, particularly in terms of global warming potential. Although AM processes involve high energy inputs and specialized feedstock, the structural benefits achieved allow for a more efficient use of materials. Overall, the study demonstrates that performance-driven design through AM reinforcements can offer a viable pathway toward more sustainable structural solutions.

Keywords: Additive Manufacturing , Environmental Performance , Hybrid Joints , Life Cycle Assessment (LCA) , Structural Optimization

3D-Printing, also known as Additive Manufacturing (AM), presents numerous opportunities for design engineers, such as fabricating complex geometries without tooling and manufacturing parts using material only where it is functionally required. Despite these advantages, one of the main challenges remains energy consumption. To assess whether AM offers superior sustainability performance compared to Traditional Manufacturing (TM), both Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) analyses are essential. While scientific literature includes various studies comparing AM with TM methods, these evaluations are often conducted using general-purpose tools. In response to this gap, the present study provides an LCA and LCC-based comparison between AM and TM for producing a motorbike brake caliper. The objective is to determine whether AM can deliver greater sustainability, from both environmental and economic perspectives, when assessed over the entire product life cycle. For AM, the analysis is conducted using a dedicated life cycle tool developed in prior research, whereas the evaluation of TM is carried out using established commercial software. The comparison deliberately excludes other considerations, such as product quality and performance. The findings indicate that AM does not emerge as the most suitable manufacturing option for this component, despite the implementation of lightweighting strategies.

Keywords: 3D-Printing , Brake , Caliper , LCA , LCC

This study presents a simulation-based optimization of the upper control arm in a transverse push-rod suspension system for a Formula SAE vehicle. The design process centers on the parametric variation of the three critical connection points that define the arm's geometry, resulting in a nine-variable configuration space. By systematically exploring this space through a Design of Experiments (DOE) framework, a Response Surface Methodology (RSM) is applied to both identify optimal geometries and assess the sensitivity of component behavior to each variable. Mechanical simulations under various dynamic conditions, such as braking, acceleration, and cornering, provide the performance data used in statistical modeling. The approach enables early-stage prediction of structural response, guiding CAD development and physical prototyping while significantly reducing trial-and-error iterations. Beyond optimization, this work offers insight into the relative influence of design parameters, supporting more informed and resource-efficient decision-making in the suspension design workflow in an early stage of product development, even before CAD prototyping.

Keywords: DOE , RSM , Suspension Geometry Optimization , Sustainable Design , Vehicle Design , Virtual Prototyping

High-performance polymers, particularly Polyetheretherketone (PEEK) and Polyetherimide (PEI), are very suitable for engineering applications due to their exceptional mechanical and thermal properties. Therefore, combining them in a single build process could be a strategic solution that can exploit the superior mechanical strength of PEEK, despite its printing challenges, while leveraging PEI's excellent surface finish and ease of printing. However, the processing challenges of these materials require careful control over printing parameters to achieve the desired part qualities. Therefore, this preliminary study aimed to define the feasible process parameter ranges for printing the parts with a multi-material infill strategy. The article focused on selecting print materials and varying three process parameters: infill pattern, infill percentage, and chamber temperature. Samples were printed using three infill patterns (rectilinear, fast, and full honeycomb), two infill percentages (40% and 100%), and three chamber temperatures (155 °C, 185 °C, and 210 °C). Tensile tests were performed, and main effect plots were used to analyze the effect of varying each process parameter on the Ultimate Tensile Stress (UTS) and elastic modulus (E) of printed parts. Based on the analysis, a reasonable range of process parameters is selected to conduct the study on investigating the feasibility of a multi-material printing strategy.

Keywords: Fused Filament Fabrication , Mechanical Testing , Polyetheretherketone , Polyetherimide , Print Process Parameters

Recent advancements in additive manufacturing have enabled the design of tailored lattice structures, suitable for a range of applications, including biomedical implants. The design of lattice structures for biomedical applications requires accurate prediction of both stiffness and strength. This study presents a numerical framework to estimate the effective elastic properties and limit stresses of periodic lattice structures using a strain energy-based homogenization method combined with an efficient method to assess limit stresses along the different directions of the lattice structures. Four cell topologies (ACC, BCC, SC-BCC, F2CC) with varying strut diameters were analysed. The effective elastic constants were computed by applying periodic boundary conditions to the representative volume element of the lattice structure. To estimate the effective limit stresses, a method based on the volume-averaged stress over a subset of the most stressed elements (Ω) was proposed. Three selection strategies for Ω were developed and evaluated through sensitivity analyses. Results show that the estimated limit stresses strongly depends on the definition of Ω. The proposed method enables early-stage design of lattice-based implants with tailored mechanical behaviour and controlled failure limits, enhancing safety and biological integration, contributing to the development of computational tools for patient-specific implant design.

Keywords: Additive manufacturing , Finite Element Analysis , Homogenization , Lattice structure , Osseointegration

This work investigates the mechanical performance of various interlocking geometries for multimaterial joints produced via Fused Filament Fabrication (FFF). The study focuses on three joining strategies: dovetail, T-shaped, and wave interlocks applied to tensile test specimens based on ISO 527 standards. Each geometry was designed in multiple configurations, varying key geometric parameters such as dovetail angles and T-stem widths. Specimens were fabricated using PET-G and, for hybrid joints, a combination of PET-G and Nylon (PolyMide CoPa). Numerical simulations were conducted employing Representative Volume Elements (RVE) to account for anisotropic behavior and layer deposition patterns. Experimental tensile tests validated the simulation results and revealed consistent plastic deformation in the female part of mechanical interlocks. In wave specimens, where adhesion was the primary joining mechanism, strength increased significantly with surface area, while thermal post-processing (annealing) negatively affected mechanical performance. Overall, the findings confirm the critical role of geometry and surface interaction in joint strength and suggest that interlocking strategies can outperform adhesive-only solutions in multimaterial 3D printing. The results pave the way for more reliable, mechanically robust designs in polymer additive manufacturing.

Keywords: Fused Filament Fabrication , Geometric joint , Interlocking , Multimaterial