Additive manufacturing

Additive Manufacturing (AM) is still considered an emerging technology, and it has proven suitable for the fabrication of complex geometries. Selecting AM to fabricate a part involves investigating the economic, environmental, and mechanical aspects of production processes. However, the role of part geometry is often neglected. Even if it is established that AM can be used to manufacture parts with complex shapes, such AM-oriented complexity has not been formally defined. Hence, this paper investigates the role of part geometry in manufacturing and the reasons behind selecting a manufacturing process. A semi-structured interview study was conducted with ten manufacturing experts. Then, the interview data was evaluated using Latent Semantic Analysis. Six questions were used in the analysis to address the objectives of the paper. Most of the responders tended to describe the manufacturing processes instead of describing the presented geometry when directly asked. The interview revealed that experts consider the material, use, geometry, part size, batch number, machine availability, mechanical properties, production cost, and part quality as fundamental criteria to select a manufacturing process.

Keywords: Design for additive manufacturing , geometric complexity , latent semantic analysis , manufacturing process selection , semi-structured interview

The primary procedures performed in maxillofacial surgery are osteotomy and repositioning. Surgeons usually exploit 3D printed guides and splints which entail considerable production time and high costs. To address these issues, innovative technologies such as mixed reality (MR) are emerging, but accuracy must still be assessed. Head-mounted displays (HMDs) are categorised into two main types: optical and video see-through. Recognisable comparisons between HoloLoens 2 (optical see-through) and Varjo XR3 (video see-through) are still not available in the scientific literature. This paper compares the accuracy of simulating maxillofacial surgery through these two different headsets. For the evaluation, a 3D model of a skull was 3D printed using Color Material Jetting 3D printing technology. Six people tested the MR application by i) tracing lines and holes with a pen following the holograms displayed on the phantom's anatomy for osteotomies, ii) moving the maxillary fragmented bone according to the projected hologram for repositioning. Times were recorded during the trial. The tested geometries were then 3D scanned to reconstruct the traced cutting lines and holes, and quantitative results were extracted in CloudCompare by comparing the drawn and nominal lines. For the repositioning, deviations have been computed to calculate the mean deviation from the planned displacement.

Keywords: Healthcare Design , Maxillofacial Surgery , Mixed Reality , Optical See-Through , Video See-Through

Stroke survivors often experience debilitating upper limb conditions, requiring therapy and rehabilitation exercises to regain limb function. However, frequent visits to medical centers for treatment sessions pose challenges. This paper presents GripDome, a prototype designed to measure grip strength in a user-friendly and highly tailorable manner, enabling strength recovery for patients in domestic environments without the need for medical assistance. GripDome consists of an elastic, inflatable silicone dome connected to a plastic base. Patients exert pressure inside the device by squeezing the dome with varying forces, which is measured using an external pressure transducer and a microcontroller. The prototype offers adjustable resistance levels, facilitating quantitative assessment of grip strength and personalized rehabilitation progress tracking.3D printing is employed for plastic components, enhancing affordability and customization. Experimental tests demonstrate GripDome's ability to distinguish forces of different intensities and repeatability of measurements.

Keywords: 3D printing , Grip Strength , Pneumatic , Rehabilitation , Soft Material

More than 90% of atrial thrombi in patients with non-valvular atrial fibrillation originate in the Left Atrial Appendage (LAA), a diverticulum of the left atrium of the human heart, whose morphology predisposes the stasis of blood within it. The Left Atrial Appendage Occlusion procedure shows promise for reducing the risk of stroke due to blood clots in the body circulation after forming in the LAA; however, it must be performed by experienced operators due to the numerous associated risks. The objective is to develop a simulator for training novice operators in the procedure to plan the optimal occlusion path on representative models. Starting from a dataset of 20 diagnostic images provided by the Azienda Ospedaliero Universitaria of Careggi, a three-dimensional reconstruction of the anatomical areas involved in the surgical procedure and their spatial identification are performed. These results are used to design a device for the adjustment of a 3D printed model of the LAA with correct orientation and spatial coordinates. The simulator is a highly customizable and patient-specific prototype system; the ease of use and small size help its acceptability and reduce the time required for practice in use.

Keywords: 3D Printing , LAA , Simulator , Surgical training

This paper presents a study focused on comparing optimization methods applied to three distinct lattice structure: Octet, FCC, and BCC. The comparison was carried out through a comprehensive review of the relevant literature using the Google Scholar database. Various factors were considered, including the additive manufacturing process and corresponding materials, the software used for structural design and simulation, the geometric parameters, and the improvement obtained. It has been observed that certain optimization techniques, such as the addition of struts, can enhance the energy absorption capacity of lattice structures by increasing their relative density. In comparison, methods such as curved lattice designs were found to alleviate stress concentrations at the nodal points, leading to a more uniform stress distribution.

Keywords: Additive manufacturing , BCC , Energy Absorption , FCC , Lattice structure , Octet

This paper explores the influence of Voronoi tessellation parameters on the dynamic behavior of a mechanical tensioner's leaf spring used in internal combustion engines. By integrating Voronoi tessellation with Additive Manufacturing, the research investigates how varying the number of seeds affects the modal frequencies of the leaf spring. The study employs a design algorithm to maintain constant mass while adjusting the number of seeds and scaling factor, using a finite element (FE) formulation to predict and manage the leaf spring's dynamic nonlinear characteristics based on mass distribution. Modal simulations extract the natural frequencies, modal shapes, and participation factors of the component, analyzing how changes in these factors impact performance. The research findings underscore the significance of Voronoi parameters in modifying natural frequencies and dynamic behavior, highlighting their potential for topology optimization in frequency-sensitive applications. Validation comes through experimental testing, confirming the simulation results and emphasizing the role of appropriate mass distribution in controlling system frequencies.

Keywords: CAE Approach , Modal Frequencies , Participation Factors , Tensioner Leaf Spring , Topology Optimization

Amongst Additive Manufacturing (AM) processes, Powder Bed Fusion (PBF) technologies represent one of the most promising production methods for polymers and metals, and the laser-based systems are certainly the technology that currently guarantee the production of metal parts with complex geometries, shapes, and mechanical properties comparable to those of parts produced using traditional methods. A functionally graded material (FGM) or a multi-material (MM) component can be advantageously produced with several processes and laser-powder bed fusion (L-PBF) is one of the metal-based process for their production and design. In this scenario, the paper proposes a procedure to manufacture FGM or MM parts with standard L-PBF machines, that is equipped with only one powder deposition system, using the 2D multi-material approach, where the material transition occurs between the layers with a material change along the building direction. Joints between materials of common interest, such as AISI 316L & CuCrZr alloy, AISI 316L & 16MnCr5 steel, and Al-Sc & AlSi10Mg alloy, were considered. The joints were analysed by means of metallographic investigation, neutron tomography (NT) analysis and tensile tests. The results of metallographic and tomography analyses highlight the continuity of joints establishing the possibility and the effectiveness to manufacture FGM or MM.

Keywords: Functionally graded material , Laser-powder bed fusion , Mechanical properties , Microstructure , Neutron tomography

Structural topology optimization approaches are widely used to create lightweight and efficient components through additive manufacturing. The race to lightweight components should also account for natural frequencies when designing components and structures subjected to dynamic loads, as in aerospace and automotive engineering. These optimization tools require extensive manual setup, mainly when tuning input parameters that govern algorithmic functions and convergence. In this context, machine learning approaches can circumvent the trial-and-error process associated with the manual setup of simulation factors. This study presents a method that utilizes machine learning to suggest optimal input parameters, such as evolutionary rate and mesh dimensions, for creating lightweight and optimized structures while maintaining a consistent natural frequency. The framework incorporates a neural network trained on a collection of previously solved, analogous problems. A dissimilarity metric derived from problem metadata is used to determine tuning parameters. This approach can be applied to analyze and optimize product configurations where only marginal conditions may change; a Bayesian optimizer based on data coming from the neural network is used to improve the structure, substituting the topology optimization algorithm and reducing the time-to-market of a specific product.

Keywords: Artificial Neural Network , Bidirectional Evolutionary Structural Optimization (BESO) , Design for Additive Manufacturing , Frequency Optimization , Topology Optimization

Lightweight design is a common way of reducing mass while enhancing the performance of mechanical components. The paper proposes a method to analyse the substitution of bulk volume with optimised lattice structures. The approach considers an early DoE analysis to explore the design space, Finite Element Analysis to evaluate the feasibility of possible design solutions, and Artificial Intelligence tools to look for optimal design solutions, including Genetic Algorithms and Response Surface Methods. To validate the methodological approach, this work proposes the design optimisation of a lightweight diesel engine connecting rod, redesigned using Triply Periodic Minimal Surface (TPMS) lattice structures where they are functionally convenient. The TPMS cells analysed are gyroid, diamond, and SplitP. Laser-Powder Bed Fusion (L-PBF) is the Additive Manufacturing process considered during the redesign phase.

Keywords: additive manufacturing , design optimisation , genetic algorithms , lightweight design , response surface methods

Additive Manufacturing techniques enable the realization of complex and free-form geometries that are difficult to realize with traditional subtractive processes. These geometries can be useful in searching for a lightweight design of existing objects. One of the main tools to achieve lightweight parts is the use of lattice structures, where the bulk volume is replaced by a pattern of unit cells. This paper presents a method to lightweight a kart connecting rod using lattice structures, with the idea of realizing this connecting rod with the L-PBF technique.

Keywords: Connecting Rod , Design for Additive Manufacturing , Kart , Lattice Structures , Lightweight Design

Additive manufacturing components are prone to defects, including warping and cracking, which can significantly impact their mechanical performance. Determining deformations in lattice structures remains challenging. This paper presents a methodological framework for computing deformation matrices in additively manufactured lattice samples using 3D scanning. The sample's geometry is acquired through 3D scanning, registered to a reference model, and vertices are determined and used for computing deformation metrics, including volumetric scaling factors, isovolumetric scaling, and angular deformations. A sensitivity analysis comparing four association criteria demonstrates the reliability of the Gaussian Best Fit Plane External. Assessing deformation in lattice structures can be useful for optimizing printing parameters and compensating for process-induced deformations.

Keywords: 3D scanners , Additive Manufacturing , Deformations , Lattice Structures

The availability of foaming materials with properties that vary according to the heat transferred to the filament in the fused filament fabrication (FFF) process provides the opportunity to develop new design methodologies that allow the exploitation of the range of characteristics offered by these materials. In this work, an integrated CAD-CAM method to realize graded density foamed components via FFF is proposed. The method consists in the post-processing of a G-code file obtained from a CAD model according to functional requirements defined by a density map volumetric model. The method relies on the material property-process parameters correlation to drive the foaming in a specific extruder configuration. The temperature effect on extrusion width and density is experimentally investigated as the primary process parameter driving the foaming behaviour of a commercially available filament. Based on the density map of the volumetric model and the experimental characterization, temperature and extrusion amount are updated in the G-code file.

Keywords: Additive Manufacturing , Design Method , Foaming , Functionally Graded Density , Fused Filament Fabrication , Polylactic Acid

This paper presents an optimization analysis of the geometrical accuracy of metal binder jetting products. An orthogonal array L9 was designed using Taguchi method to study four process parameters (printhead speed, dark body, powder applicator speed and shell thickness) at three levels. Printed parts were measured by a coordinate measuring machine, and parallelism error was evaluated, both in planes aligned with binder injection and with powder spreading direction. Samples geometry was characterized by a squared through hole to evaluate differences in external and internal features. In the nine experiments, the parallelism varied in a range between 0.01 and 0.04 mm. No significant difference was observed in relation to plane direction and feature type, while parallelism tended to decrease with the increase in the sample's distance from the printing platform. A grey relational analysis was employed to optimize process parameters, in order to improve the geometrical accuracy. Through the analysis of means of grey relational grade, it was found that powder applicator speed has the highest effect on response variables, while printhead speed has the lowest contribution.

Keywords: Binder Jetting , Geometrical accuracy , Taguchi method

Conventional ground-based transport systems often experience delays due to congested traffic. This is unacceptable in the case of transporting organs, blood, medicines and emergency supplies, when time is critical. Urban Air Mobility (UAM) offers a solution to overcome transportation inefficiencies. In fact, Unmanned Aerial Systems (UAS) can quickly reach remote locations providing critical care in a timely manner. However, ensuring efficiency, safety and compliance with regulations is essential. This paper presents the mission-oriented design approach of a UAS, focusing on two subsystems, namely the Unmanned Aircraft (UA) and the Functional Container (FC). The design of the UA involves choices for configuring its layout. The FC design focuses on the preservation of the transported material. Lightweight and reliable dedicated solutions are designed for FC leveraging Additive Manufacturing (AM) technology. The design is mission-oriented, but allows systems to be reconfigured for additional missions.

Keywords: Advanced air mobility , Drone , medical , mission-oriented design , Unmanned air vehicle

Industry 5.0 emphasizes human-centric approaches in technological advancement, particularly crucial in healthcare applications such as prosthetics development. While individual technologies like additive manufacturing, machine learning, digital twins, and tissue engineering have shown promise in prosthetics innovation, their integration remains a significant challenge. This paper presents a novel multidisciplinary framework developed through the National Centre for High-Performance Computing (CN-HPC) project, which addresses the gap between individual technological capabilities and their coordinated application in personalized prosthetics development. The framework, implemented through collaboration between six research groups from two universities, employs the House of Quality methodology to align technological integration with patient needs. Our approach encompasses a comprehensive seven-step process, from initial patient requirements definition through virtual modeling, production process optimization, virtual sensing, machine learning enhancement, digital twin simulation, to advanced tissue engineering. A data model facilitates seamless information exchange between different technological domains and research groups. This research contributes to the field by providing a scalable, human-centered framework for technology integration in medical device development, potentially extending beyond prosthetics to other healthcare applications. The proposed framework represents a significant step toward realizing the full potential of Industry 5.

Keywords: Healthcare , House of Quality , Human-Centricity , Industry 5.0 , Prosthesis

The environmental and economic sustainability of Additive Manufacturing (AM) is an aspect that deserves attention. Proper design frameworks must guide design engineers in conceiving sustainable AM products during the conceptual design phase. Previous scientific studies are not grounded on the lifecycle engineering (LCE) approach since they consider only specific product lifecycle phases (e.g., manufacturing or end-of-life) or are based on the general design for AM guidelines, not considering sustainability drivers (cost and environment). This paper presents an innovative ecodesign for AM framework called eDAM. First, it allows designers to evaluate if and when AM is sustainable from a LCE perspective. Secondly, it enables design engineers to maximize product lifecycle performance by optimizing the adoption of the unique benefits of AM. The eDAM framework was used to re-design a passenger aircraft's interior panels and spacers. Using a bio-inspired shape, designers achieved a 15% weight reduction on the part and 0.

Keywords: Additive manufacturing , Ecodesign , Lifecycle engineering , Sustainability

The objective of this project is to address the limitations of conventional slicing and simulation software in the field of 3D printing. The project entails the creation of a comprehensive virtual environment utilising the Unity platform, thereby effectively integrating the capabilities of G-code generation programs with the precision of 3D models. By employing this innovative approach, the project has achieved a high degree of accuracy in simulating the movements of actual printing machinery and accurately representing material deposition processes. A key objective is the creation of a dynamic and interactive framework that can accommodate a wide range of inputs and sensory data in real time. This feature enhances the Virtual Twin technology, transforming it into a highly versatile tool for conducting simulations, improving printing efficiency, and facilitating advanced technical training. The significance of this project lies in its immediate practical applications and its potential to serve as a pioneering model for future developments within the 3D printing industry and beyond.

Keywords: 3D Model , 3D printing , Codification , Virtual Twin

This paper presents a method for designing a customized ergonomic office chair backrest aimed at improving user posture and long-term health. Given the importance of ergonomics in workplace settings, this study leverages 3D scanning and additive manufacturing to create personalized cushions that conform precisely to individual anatomical shapes, aligning with ergonomic standards. The process begins with high-resolution scans of both the user's back and a standard chair backrest, followed by cushion modeling in Blender to ensure exact fit and support. Additive manufacturing was selected for cushion fabrication, using a TPU material with an optimized internal structure to enhance comfort. Results indicate a notable improvement in posture alignment and comfort, verified through comparative scans before and after customization. The custom backrest also encourages proper posture through a postural retraining effect and provides a high level of hygiene due to its non-porous material.

Keywords: Additive manufacturing , Custom cushion , Ergonomic chair

In orthopedic surgery, bone tissues aid in the reconstruction of damaged or missing bone and ligaments, allowing patients to achieve optimal motor function recovery. A musculoskeletal tissue bank collects and certifies donated tissue for transplantation. However, sometimes suitable bone tissue is unavailable or incompatible geometrically with the required implant. Custom-made, biocompatible artificial bone tissue development could mitigate such challenges. Scaffolds, either biological or synthetic, promote bone regeneration within the body. Despite research on their chemical compositions and mechanical properties, limited attention is given to their geometric design and personalized shape. This study presents a method for designing bone scaffold geometry using additive manufacturing in a biocompatible material. The aim is to create a scaffold with variable density, from denser cortical to less dense medullary zones. CT images determine bone tissue density, compared to the density imposed on the scaffold. Additionally, the printability of the PEEK, the chosen material, is investigated.

Keywords: 3D Printing , Biomaterials , CAD , Lattice structures , PEEK

Geometric Dimensioning and Tolerancing (GD&T) are among the basic concepts of functional fitness and quality assurance in modern manufacturing. The historical development of GD&T took place primarily in the ambit of subtractive manufacturing; the advent of Additive Manufacturing (AM) now presents novel challenges due to the complexity of geometries, material variability, and process-induced variances. The present Perspective Paper briefly hints at key challenges for the future of GD&T in AM, with an eye to the necessary adaptation of tolerancing principles to AM-specific geometries, integration of Model-Based Definition (MBD) in digital threads, and development of new standards for surface texture and tolerance stack-up. New inspection techniques are also highlighted for the AM parts, which would become more prominent.

Keywords: additive manufacturing , geometric dimensioning and tolerancing , ISO , model-based definition , surface texture features