Additive manufacturing

Robot-based additive manufacturing (RBAM) is an additive manufacturing (AM) technology powered by robotic manipulators. The material is deposited from a nozzle onto an initial surface, adding successive layers on top of each other and pouring it along multiple directions (multiaxial deposition) thanks to the dexterity of robots, often of the anthropomorphic type. Furthermore, it is possible to manufacture layers of non-uniform thickness, thus obtaining non-parallel and non-planar layers. In particular, RBAM can be implemented to realize revolved parts with protruding portions. Cylindrical or conical slicing algorithms have been devised to process the sub-volumes, reducing the number of layers and the need for support structures. In this context, the paper presents a novel algorithm for non-uniform cylindrical slicing that processes sub-volumes connected to a cylindrical shape. The specific contribution of the work is an algorithm that moves from a curved slicing to increase the adhesion between the central body and the first layer, and it relaxes the curvature in the subsequent layers, arriving, if possible, at a planar slicing. The algorithm considers robots' intrinsic constraints on movements. Planar paths are better approximated than non-planar ones since they prevent the robot from constantly changing the nozzle angle, thus increasing the overall quality of the printing. The algorithm is applied to four test cases and compared with other slicing approaches using numeric indices, objectivating its strengths and limits.

Keywords: Cylindrical slicing , Non-planar slicing , Non-uniform slicing , Robot-based additive manufacturing

Additive Manufacturing (AM) technologies are widely spreading into multiple engineering sectors thanks to their flexibility to create complex geometries with virtual no material waste. AM technologies capabilities can be fully exploited when working with periodic lattices, creating topology-optimized structures through different cell types with different dimensions and volume fractions. Several factors (i.e., process parameters, quality and type of raw materials) can modify the mechanical properties of printed components and can be exploited to selectively create functionally graded materials or conventional laminated hybrid materials structures. This paper analyses and compares the mechanical properties of different additively manufactured lattice BCC structures through experimental and numerical means. At first, the manufacturing procedure followed by experimental tests is presented. The retrieved mechanical properties are then used as a benchmark for the numerical Finite Element Analyses and compared with analytical models available in the literature. The numerical simulation campaign includes the comparison of a full 3D model and a 1D/2D beam/shell formulation model. The research findings demonstrate a good correlation between the experimental tests and the numerical simulation results, indicating the potential for the proposed methodologies to be broadly implemented within various domains of structures and materials.

Keywords: 3D lattice , Additive Manufacturing , Design for Manufacturing , FEM , Periodicity

The widespread and diversified use of portable devices with high magnification power at relatively low-cost, i.e., the so-called USB digital microscopes, has revealed the possibility of employing their photographic output in Structure from Motion processes for sub-millimetric digitisation. However, USB microscopes, born for two-dimensional inspection – if used without specific accessories, designed ad-hoc for the photogrammetric capture phase – can pose some difficulties for the surveyor in managing capture operations. Thus, this study suggests prototyping a low-cost, complete, and portable mounting compatible with the most common USB microscopes for image scanning. This system makes it possible to use portable USB microscopes for three-dimensional modelling at a low-cost, as it is easy to replicate both in terms of construction and the materials used. Therefore, through the interaction of several skills, the work shows how the photogrammetric process can also be made accessible to devices that were not initially designed for such application, paving the way for new paths in representation engineering research.

Keywords: Additive Manufacturing , Fast Survey , Structure from Motion

Nowadays the interest for improving methodologies to design customized external devices for the neck has considerably grown, considered that neck pathologies are widespread among the population. Their design for additive manufacturing starts by acquiring the body's part and, in order to achieve a satisfactory end result, the support of accurate reconstructed models from fast scans is relevant. At this aim, the availability of an average or statistical model could be potentially useful for reducing acquisition time and for upgrading low-resolution scans. This paper focuses on the application of a methodology for the creation of an average model of human neck. The method required the use of a set of scans, acquired by means of a structured light scanner, from which an accurate reconstruction of the neck surface was obtained. A number of healthy subjects of both genders was considered and the digital neck surfaces were used for creating an average digital model for males and for females. The methodology developed was based on mesh morphing and was applied to the sample considered with satisfactory results. The procedure is also suitable for the development of statistical models of the neck, that will cover future research

Keywords: Acquisition , Mesh morphing , Neck , Reverse Engineering

3D printed patient-specific hand orthoses can improve the efficiency of the treatment and the comfort of the patient, but since each customized orthosis is a virtually unique device, it is difficult to assess their mechanical response in the design phase, both experimentally and numerically. The Finite Element Method (FEM) could be used to predict the deformation of the orthosis under predetermined loads, but patient-specific models including interaction with the hand are still lacking. In the present work we present a computational model in which, starting from the scan data of the hand used to manufacture the orthosis, a FEM model of the hand is generated, including a skeletal structure. Hand bones positions and dimensions can be defined basing on simple anatomical measurements or literature data and the stiffness of the joints can be tuned in relation to patient pathology. The remaining hand volume consists of a soft tissue region, mimicking the non-linear mechanical behaviour of skin and muscles. Results show that both functional and structural indexes can be analyzed, such as contact pressures, stress state or the compliance of the orthosis, providing useful information for the design of custom devices. By using mesh deformation algorithms, the scan data could be used to generate different orthosis designs in target positions defined by the therapist and, taking advantage of a parametric model under development, the skeletal structure could be adapted correspondingly, providing an innovative pathway to investigate the response of the orthosis during the whole rehabilitation.

Keywords: 3D Printing , FEM , Hand Orthosys

The current study presents the development and validation of a compliant Delta robot with a monolithic structure, which has been fabricated using additive manufacturing (AM). The monolithic design and the use of AM accelerate the robot development cycle by enabling rapid prototyping and deployment while also facilitating experimentation with novel or different robot kinematics. The use of flexible joints for robots presents a challenge in achieving sufficient workspaces. However, parallel architectures are well suited for incorporating compliant joints, as they require lower ranges of motion for individual joints compared to serial architectures. Therefore, the Delta configuration has been chosen for this study. Multibody flexible dynamics (MfBD) simulations have been used as a means to guide design choices and simulate the structural behaviour of the robot. A design for additive manufacturing (DfAM) technique has been adopted to minimize the need for support structures and maximize mechanical strength. The quantitative evaluation of the Delta's overall performance has been conducted in terms of stiffness and precision. The stiffness test aimed to gauge the robot's ability to withstand applied loads, whereas the repeatability test assessed its precision and accuracy. This approach offers a promising path for robot design with significant potential for future advancements and practical applications while highlighting the trade-offs that designers should consider when adopting this methodology.

Keywords: additive manufacturing , compliant mechanisms , monolithic design , parallel robots

In a technological context where, thanks to the additive manufacturing techniques, even sophisticated geometries as well as surfaces with specific micrometric features can be realized, we propose a mechano-regulation algorithm to determine the optimal microgeometric parameters of the surface of textured titanium devices for biomedical applications. A poroelastic finite element model was developed including a portion of bone, a portion of a textured titanium device and a layer of granulation tissue separating the bone from the device and occupying the space between them. The algorithm, implemented in the Matlab environment, determines the optimal values of the root mean square and the correlation length that the device surface must possess to maximize bone formation in the gap between the bone and the device. For low levels of compression load acting on the bone, the algorithm predicts low values of root mean square and high values of correlation length. Conversely, high levels of load require high values of root mean square and low values of correlation length. The optimal microgeometrical parameters were determined for various thickness values of the granulation tissue layer. Interestingly, the predictions of the proposed computational model are consistent with the experimental results reported in the literature. The proposed algorithm shows promise as a valuable tool for addressing the demands of precision medicine. In this approach, the device or prosthesis is no longer designed solely based on statistical averages but is tailored to each patient's unique anthropometric characteristics, as well as considerations related to their metabolism, sex, age, and more.

Keywords: Additive manufacturing techniques , Correlation length , Mechanobiology , Optimal surface roughness , Root mean square

This paper presents an image clustering algorithm that classifies parts to be fabricated using traditional and additive manufacturing (AM) technologies. The proposed algorithm is a MATLAB-based software tool that clusters 3D CAD models of parts considering their geometry only. The algorithm can classify image datasets, CAD datasets, and combined datasets that contain both images and CAD models. The software tool reduces the time and effort spent during process selection by offering a preselected set of parts that are more suitable for AM. The software tool is aimed at supporting decision-making for traditional manufacturing companies that consider expanding their production capability by introducing AM processes in their production facilities. The HICA software tool expands the scope of scientific applications in manufacturing process selection by providing an unsupervised approach that does not require data labelling. The tool is made available as a MATLAB function through a permanent link.

Keywords: Additive manufacturing , CAD , Hierarchical clustering , Image processing , MATLAB , Process selection , SolidWorks

This work investigated the impact and piercing load resistance (energy absorption capabilities) of 3D-printed composites plates manufactured by means of the Fused-Filament-Fabrication (FFF) technique. Two sets of reinforced composite plates were produced. The first set of plates was printed with short-carbon-fiber-reinforced polyamide-12, while the second set was reinforced with continuous fibers. The plates were tested with quasi-static indentation tests at various Span-to-Punch ratios and with three different indenter nose shapes (blunt, hemispherical, and conical). The quasi-static measurements were subsequently elaborated to estimate the energy absorption capability of the plates during a ballistic impact. The addition of continuous fibers increased the quasi-static energy absorption capability by 20–185% with respect to the short-fiber-reinforced plates. The quasi-static results showed that by including the continuous reinforcement in the plates, the normalized energy absorbed increased by an order of magnitude. Finally, a comparison with data from the literature concerning continuous-reinforced composite plates manufactured by means of traditional techniques was carried out. The comparison revealed that FFF-printed composite plates can compete with traditional composite ones in terms of both ballistic and quasi-static penetrating load conditions, even if limited by the lower fiber volume fraction. Thus, these findings confirm that this novel Additive Manufacturing technique is promising and worth investigating further.

Keywords: Additive Manufacturing , composite plate , continuous fibers , Fused-Filament-Fabrication , impact , quasi-static indentation test , short fibers

Radical technological innovations are emerging in response to environmental, economic and geopolitical pressures. This affects how we design and manufacture new solutions. Additive manufacturing, one of the enabling technologies of the digital transition, can support more-sustainable manufacturing processes if developed through a system-level approach. In this Perspective, we adopt such an approach: we propose to use established sustainable design methods to innovate additive manufacturing systems and to consider how to make additive manufacturing an enabler of sustainable design in combination with conventional manufacturing. We then discuss how to implement our vision to enable additive manufacturing for sustainability

Current technological developments in the field of sensor capture and additive manufacturing (AM) from computer models have led to innovative solutions for a 3D reconstruction of anatomical parts of the human body in real time, enabling interesting applications in the medical field and especially in orthopedics. The following work proposes the use of new technologies applied to tele-rehabilitation so that the patient can benefit from remote rehabilitation services. The wrist motion performed by the physical therapist was to be compared with the wrist motion of the patient undergoing rehabilitation, so as to obtain a proper analysis on the treatment to be followed, the expected timing and the recovery goals. Future applications could involve the use of the proposed system within hospitals and rehabilitation centers in order to support health care providers, improve patient care and quality of life, and contribute to the innovation of new approaches for medical assessment.

Keywords: Acquisition , Flexion-Extension , Radial-Ulnar deviation , Rehabilitation , Wrist

This paper provides an up-to-date overview of the technologies used today in the field of Additive Manufacturing (AM). For each type of process, it is outlined which techniques are most often used and which are the most suitable materials for the development of the AM process. The latest technologies are analysed, highlighting their potential, accuracy and ability to create complex geometric features that are difficult, or impossible, to achieve by conventional processing techniques. Finally, some case studies developed by the authors dealing with lattice structures with high ratios of mechanical characteristics / porosity are presented. For these applications, the most proper AM technologies and the most performing materials, that provide accurate solutions, were evaluated.

Keywords: Additive Manufacturing , FDM techniques , High porosity , Lattice structures , Rapid Prototyping process

The topology optimization methodology is widely utilized in industrial engineering for designing lightweight and efficient components. In this framework, considering natural frequencies is crucial for adequately designing components and structures exposed to dynamic loads, as in aerospace or automotive applications. The scientific community has shown the efficiency of Bi-directional Evolutionary Structural Optimization (BESO), showcasing its ability to converge towards optimal solid-void or bi-material solutions for a wide range of frequency optimization problems in continuum structures. However, these methods show limits when the complexity of the domain volume increases; thus, they are well-suited for academic case studies but may fail when dealing with industrial applications that require more complex shapes. The connectivity of the structures resulting from the optimization also plays a fundamental role in choosing the best optimization approach, as some available commercial and open-source codes nowadays return unfeasible sparse structures. An improved voxel-based BESO algorithm has been developed in this work to cope with current limits in lightweight structure optimization. A significant case study has been developed to evaluate the performances of the new methodology and compare it with existing algorithms. In contrast to previous studies, the method we developed guarantees that the final structure respects constraints on the initial design volume and that the structure's connection is preserved, thus enabling the manufacturing of the component with Additive Manufacturing technologies. The proposed approach can be complemented by smoothing algorithms to obtain a structure with externally appealing surfaces.

Keywords: Additive manufacturing , Bi-directional evolutionary structural optimization (BESO) , Natural frequency , Optimal design , Topology optimization

Over the past few decades, the scientific community's and industry's interest in additive manufacturing technologies has surged. This technology is distinguished by the layer-by-layer deposition of the raw materials and the piece's growth in a predetermined build orientation. This factor impacts the process' overall cost, surface quality, and other crucial parameters. Numerous methods to solve competing aspects have been proposed in the literature, with the more promising that iteratively uses ray-tracing techniques. Existing algorithms iterate for each discrete element of the model's bounding box projection onto the building platform. However, when optimisation algorithms are used on real-life industrial parts, computational time problems arise due to the high number of faces in the models. A new computational technique to determine the appropriate part orientation to reduce the support volume is proposed to address the problem. The method reduces the computational time, cycling the ray-tracing only on the triangles where the model surface is discretised. This approach has been integrated into an enhanced particle swarm optimisation algorithm to prove its efficiency. The approach is intended for industrial applications where it is necessary to handle complicated geometries quickly and efficiently to find the best orientation. Based on the computer's resources and the complexity of the faceted model, a set of case studies with an industrial engineering significance is used to demonstrate the approach's effectiveness.

Keywords: Additive manufacturing , Build orientation , Part orientation , Particle swarm optimisation , Support material

The increasing emissions of greenhouse gases (GHG) and pollutants like particulate matter and nitrogen oxides (NOx) have led to environmental concerns. Hybrid and electric powertrains are being introduced as means to reduce pollutant emissions, especially at the local level. Additionally, the finite availability of fossil fuel sources, which are used to produce gasoline and diesel, highlights the need for alternative technical solutions. One approach to partly address these issues is lightweighting, which involves reducing the weight of vehicles to minimize their impact during the use phase. Mathematical models are employed to simulate the longitudinal dynamics of vehicles and estimate the energy required to accomplish driving missions. Appropriate metrics have been developed to quantify energy-saving effects that, in addition, can support the decision making, design, and development phase of future vehicles. To facilitate this process, it would be useful to build a database of ERV (Energy Reduction Value) and FRV (Fuel Reduction Value) figures derived through a unified procedure. Such a database would be useful in evaluating the effectiveness of vehicle lightweighting and its impact on energy consumption and pollutant emissions. The last phase of the analysis is the assessment of the overall reduction in the environmental impact of the vehicle throughout its life cycle by using the LCA (Life Cycle Assessment) approach. From this study, it was possible to conclude that lightweighting can be an appropriate solution to improve the energy efficiency of vehicles and that appropriate metrics, can support the development of new car models. The potential to integrate enhanced energy efficiency, lower emissions, and higher safety features into our everyday vehicles would represent a significant advancement in the automotive industry. There is a gap in the scientific literature on the effects of lightweighting on vehicle dynamics and energy usage which deserves to be investigated.

Recent advancements in additive manufacturing technologies have significantly enhanced the capacity to accurately reproduce the shape and material properties found in nature. Furthermore, the behavior and functionality exhibited by natural systems can be effectively simulated using bio-inspired algorithms. An essential parameter that governs various life processes is the surface area to volume ratio. In industrial applications such as catalysis and heat exchange, this particular characteristic is intentionally augmented to enhance overall performance, thus fulfilling the functional requirements. In this study, a curve differential growth implementation was developed to obtain space-filling and self-avoiding paths. By applying successive iterations of the algorithm to an initial curve, a set of curves was generated. These curves were then organized in three-dimensional Euclidean space and combined into a NURBS surface. As a case study, the design of a coaxial counterflow heat exchanger employed the proposed modeling algorithm. The resulting model underwent a numerical simulation to assess the heat transfer rate and pressure drops. Material extrusion technology was used to manufacture a prototype for preliminary demonstration, although further studies are required to ensure watertight functional parts. Numerical results indicate that the proposed design exhibits a better heat transfer rate in a smaller size but leads to higher pressure drops when compared to three equivalent plain pipe solutions (with matching length, surface area, and heat transfer rate).

Keywords: Additive Manufacturing , Bioinspiration , Biomimicry , Differential Growth , Geometric Modeling , Space-Filling Curves

Multi-material additive manufacturing enables the opportunity to combine multiple materials within the same part, allowing for an expanded range of properties that can gradually change inside the design space. This category of materials is commonly referred to as functionally graded materials (FGMs). However, FGMs currently face several limitations and challenges in terms of design and manufacturing, such as compatibility, distribution design, and prediction of mechanical properties. Furthermore, when dealing with parts possessing complex micro/meso-structures, finite element simulation often becomes a costly and time-consuming process. Among various additive manufacturing technologies, fused filament fabrication allows the combination of multiple thermoplastic materials within the same nozzle during the deposition process, thereby creating FGMs. This process, known as coextrusion, enables the gradual deposition of materials adjacent to each other while changing their fractions. Moreover, the deposition direction shapes the distribution of materials within each deposited layer, influencing the material structure and the resulting mechanical properties. A recent study proposes a preliminary model describing the deposition mechanism, which has been confirmed by experimental tests. This model delineates the section of the material deposited based on the tool path and process parameters, such as layer thickness and hatching space. To expand upon these findings, this paper applies a homogenization approach based on finite element analysis to the deposition model. This approach enables the description of material mechanical properties based on the material fractions, tool path, and other process parameters. Additionally, this study presents a methodology to tailor the mechanical properties according to the printed part's orientation around the print bed.

Keywords: FFF , FGM , Functionally graded materials , Fused Filament Fabrication , Homogenization , Multi-material coextrusion , Representative Volume Element , RVE

Using theory and simulations, the challenge of gravity-induced distortions during sintering is addressed and a mitigation strategy is proposed. Based on the continuum theory of sintering, the finite element simulation demonstrates the advantages of a rotating furnace to counteract gravity forces during sintering. Its application for stainless steel hollow parts produced by additive manufacturing (binder jetting) is demonstrated, numerically, for reliable industrial production of complex shapes. Sintering a tube in a very slow rotating motion exhibits an improvement in the final deformation ratio compared to a conventional sintering process. The same concept has been adapted for higher furnace revolution speeds and the centrifugal force is now surpassing the effects of gravity. An extended study of sintering under microgravity for space-borne applications is also widely depicted with the same model. Indeed, it shows the possibility of reproducing Earth's sintering conditions at places where gravity is insufficient to provide acceptable densification and shape conservation during sintering.

Keywords: Binder jetting , Deformation , Finite element methods , Rotating sintering , Sintering

Composite materials, pioneered by aerospace engineering due to their lightness, strength, and durability properties, are increasingly adopted in the high-performance automotive sector. Besides the acknowledged composite components' performance, enabled lightweighting is becoming even more crucial for energy efficiency, and therefore emissions along vehicle use phase from a decarbonization perspective. However, their use entails energy-intensive and polluting processes involved in the production of raw materials, manufacturing processes, and particularly their end-of-life disposal. Carbon footprint is the established indicator to assess the environmental impact of climate-changing factors on products or services. Research on different carbon footprint sources reduction is increasing, and even the European Composites Industry Association is demanding the development of specific Design for Sustainability approaches. This paper analyzes the early strategies for providing low-carbon aerospace and automotive composite components by design. The goal is to enable design approaches that consider the material life cycle from product and process design, material selection and fabrication, to eventual recycling and reuse. The investigation includes the design approaches and tools, and the aspects concerning ultimate trends of materials development, shapes generation, and manufacturing processes. Among these, we discuss the potential role of emerging technologies such as digital intelligence, Biocomposites, biomimicry, generative AI, and additive manufacturing. The aim is to identify the framework of possible drivers for Design for Sustainability approaches, rethinking lightweight products lifecycles and highlighting the resulting challenges and future developments. Moreover, as practical examples, a few innovative cases are provided to prove the effective potentials of such guidelines. The conclusive remarks discuss the advantages and disadvantages of the design drivers and the need for assessment and validation through vehicle Life Cycle Assessment approaches.

Selective Laser Melting (SLM) technology is an additive manufacturing (AM) technique that involves selective or localized melting of metallic powder bed by a high-intensity laser beam source. This technology is responsible for an induced anisotropy in the printed components: in fact, depending on the orientation of the part within the powder bed, different mechanical properties are usually obtained. It is also known that mechanical properties may depend on the rate of load application. This work studies the mechanical anisotropy induced by SLM technology on a 16MnCr5 case hardening steel subjected to high strain rate loading. A direct Split Hopkinson Bar was employed for testing. The Cowper-Symonds model was used to describe the material behavior at high strain rates for samples loaded in the building and in the normal to building directions.

Keywords: High Strain Rate , Material Anisotropy , SLM