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In order to supply auto parts to the automotive industry the companies must meet all Advanced Product Quality Planning (APQP) requirements. One of the biggest difficulties in obtaining the approval of the APQP is in the preparation of the "Master Sample," which will be used for the validation of jigs, production, and dimensional control devices. The procedures for manufacturing Master Samples through conventional manufacturing processes are outdated, slow, and cost-effective, which goes against the concepts of Industry 4.0. Therefore, this work aims to propose a procedure for Design for Additive Manufacturing (DFAM) that analyzes the feasibility and systematizes the manufacture of Master Sample through Additive Manufacturing (AM). Two model parts were submitted to the procedure, manufactured by AM and validated as Master Samples. In this work, a comparative analysis between the parts produced conventionally and those produced by AM showed that the time and costs in order to obtain the Master Samples using the proposed procedure was significantly shorter. The reduction in time to obtain Master Samples speeds up the evaluation and validation of control devices from suppliers, can speed up the acquisition of APQP documentation and reduce the time in the development of the serial parts by manufacturing process. Furthermore, the use of the proposed DFAM procedure is innovative in the context of the automotive industry, as it suggests a change in the production concept and inserts AM as another option in the manufacturing process and not just as a rapid prototyping tool. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) has revolutionized the design and production of complex geometries by offering unprecedented creative freedom over traditional manufacturing. Despite its growing prominence, AM lacks automated and standardized design rules tailored to specific AM processes, resulting in time-consuming and expert-dependent manual verification. To address these limitations, this research introduces a novel design for additive manufacturing (DfAM) framework consisting of two complementary models designed to automate the design process. The first model, based on a decision tree algorithm, evaluates part compliance with established AM design rules. A modified J48 classifier was implemented to enhance data mining accuracy by achieving a 91.25% classification performance accuracy. This model systematically assesses whether input part characteristics meet AM processing standards, thereby providing a robust tool for verifying design rules. The second model features an AM design rule engine developed with a Python-based graphical user interface (GUI). This engine generates specific recommendations for design adjustments based on part characteristics and machine compatibility, offering a user-friendly approach for identifying potential design issues and ensuring DfAM compliance. By linking part specifications to various AM techniques, this model supports both researchers and engineers in anticipating and mitigating design flaws. Overall, this research establishes a foundation for a comprehensive DfAM expert system. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) has become a key topic in the manufacturing industry, challenging conventional techniques. However, AM has its limitations, and understanding its convenience despite established processes remains sometimes difficult, especially in preliminary design phases. This investigation provides a hybrid multi-criteria decision-making method (MCDM) for comparing AM and conventional processes. The MCDM method consists of the Best Worst Method (BWM) for the definition of criteria weights and the Proximity Index Value (PIV) method for the generation of the final ranking. The BWM reduces the number of pairwise comparisons required for the definition of criteria weights, whereas the PIV method minimizes the probability of rank reversal, thereby enhancing the robustness of the results. The methodology was validated through a case study, an aerospace bracket. The candidate processes for the bracket production were CNC machining, high-pressure die casting, and PBF-LB/M. The production of the bracket by AM was found to be the optimal choice for small to medium production batches. Additionally, the study emphasized the significance of material selection, process design guidelines, and production batch in the context of informed process selection, thereby enabling technical professionals without a strong AM background in pursuing conscious decisions. [ABSTRACT FROM AUTHOR]

The innovative approach used for the design and fabrication of a UAV tails through additive manufacturing (AM) completely changes the concept of designing and manufacturing products through conventional methods. AM based processes can reduces costs, lead times, and increases design freedom, allowing parts to be tailored to specific needs. A key benefit of AM processes is the ability to produce optimized designs with reduced mass and without compromising structural effectiveness. This is possible thanks to the combination of high‐performance AM materials and the extraordinary manufacturing capability of AM technologies combined with an appropriate design‐for‐additive manufacturing (DfAM) approach, overcoming traditional manufacturing techniques. This article presents the development process of a UAV tails, based on a Design for Additive Manufacturing (DfAM) approach in order to reduce structural mass and guarantee safe operation under service loads. Therefore, by replacing the metallic component of the UAV with a techno‐polymeric one, several configurations have been developed. The optimal additive configuration achieved a weight reduction of 60% compared to a metal configuration of equivalent volume, without loss of mechanical properties. In conclusion, a feasibility study of the proposed configuration was carried out by 3D printing the vertical tail redesigned. Highlights: An innovative approach by combining DfAM processes with FFF technology.Metal replacement of UAV tails with advanced technopolymers.Efficient Weight Reduction about 60% compared to metal structure.Single‐piece design simplifies assembly and manufacturing.UAV redesigned tails with enhanced efficiency, adaptability, and feasibility. [ABSTRACT FROM AUTHOR]

The use of additive manufacturing techniques in the development of aerospace components is gaining ground. These innovative methodologies facilitate the proposal of new designs for components with weight reduced features without compromising their mechanical properties. This results in lower fuel consumption and emissions. The present paper focuses on a metal replacement process in a UAV's vertical tail, using a Design for Additive Manufacturing (DfAM) strategy and making use of the lightweight, high‐strength engineering polymer known as carbon PA. By comparing the results achieved through numerical simulations conforming to certification standards between the metal and carbon PA vertical tail model, this work points out the possibility of decreasing the structural mass of the component by up to 48% while maintaining structural integrity. This reduction is achieved by matching materials, design concepts, and manufacturing capabilities. [ABSTRACT FROM AUTHOR]

In the development of innovative and high-performance products, design expertise is a critical factor. Nevertheless, novel manufacturing processes often frequently lack an accessible comprehensive knowledge base for product developers. To tackle this deficiency in the context of emerging additive manufacturing processes, substantial design knowledge has already been established. However, novel additive manufacturing processes like continuous fiber-reinforced material extrusion have often been disregarded, complicating the process's wider dissemination. The importance of design knowledge availability is paramount, as well as the need for user-friendly design knowledge preparation, standardized structure, and methodological support for accessing the accumulated knowledge with precision. In this paper, we present an approach that provides formalized opportunistic and restrictive design knowledge, ensuring both the comprehensive exploitation of process-specific potentials and the consideration of restrictive limitations in the construction of components. Opportunistic knowledge, presented as principle cards, is systematically derived, prepared, and made accessible. Moreover, an access system is developed to ensure the comprehensive utilization of process-specific potentials throughout the development process. Furthermore, we propose linking these principles through a synergy and conflict matrix, aiming to consider synergistic principles and identify potential conflicts at an early stage. Additionally, an approach to provide restrictive design knowledge in the form of a design rule catalog is proposed. The application of the knowledge system is demonstrated exemplarily using a weight-optimized component. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) has revolutionized the design and production of complex geometries by offering unprecedented creative freedom over traditional manufacturing. Despite its growing prominence, AM lacks automated and standardized design rules tailored to specific AM processes, resulting in time-consuming and expert-dependent manual verification. To address these limitations, this research introduces a novel design for additive manufacturing (DfAM) framework consisting of two complementary models designed to automate the design process. The first model, based on a decision tree algorithm, evaluates part compliance with established AM design rules. A modified J48 classifier was implemented to enhance data mining accuracy by achieving a 91.25% classification performance accuracy. This model systematically assesses whether input part characteristics meet AM processing standards, thereby providing a robust tool for verifying design rules. The second model features an AM design rule engine developed with a Python-based graphical user interface (GUI). This engine generates specific recommendations for design adjustments based on part characteristics and machine compatibility, offering a user-friendly approach for identifying potential design issues and ensuring DfAM compliance. By linking part specifications to various AM techniques, this model supports both researchers and engineers in anticipating and mitigating design flaws. Overall, this research establishes a foundation for a comprehensive DfAM expert system.

Additive manufacturing (AM) has become a key topic in the manufacturing industry, challenging conventional techniques. However, AM has its limitations, and understanding its convenience despite established processes remains sometimes difficult, especially in preliminary design phases. This investigation provides a hybrid multi-criteria decision-making method (MCDM) for comparing AM and conventional processes. The MCDM method consists of the Best Worst Method (BWM) for the definition of criteria weights and the Proximity Index Value (PIV) method for the generation of the final ranking. The BWM reduces the number of pairwise comparisons required for the definition of criteria weights, whereas the PIV method minimizes the probability of rank reversal, thereby enhancing the robustness of the results. The methodology was validated through a case study, an aerospace bracket. The candidate processes for the bracket production were CNC machining, high-pressure die casting, and PBF-LB/M. The production of the bracket by AM was found to be the optimal choice for small to medium production batches. Additionally, the study emphasized the significance of material selection, process design guidelines, and production batch in the context of informed process selection, thereby enabling technical professionals without a strong AM background in pursuing conscious decisions.

Purpose: The work aims to propose a comprehensive design framework for additive manufacturing and apply it to a case study of the height adjuster handle of a car. The aim is to provide designers and engineers with a practical example of how the framework can be used to design a complex part for additive manufacturing. The article also aims to demonstrate the potential benefits of additive manufacturing in the automotive industry, such as improved performance, reduced times, and cost savings. Additionally, the article aims to compare the developed framework with existing design for additive manufacturing (DFAM) methodologies and highlight its unique features and advantages in designing the height adjuster handle. Design/methodology/approach: The study used qualitative and quantitative data collection and analysis methods. The first phase of the study involved a systematic review of existing DfAM methodologies and a critical analysis of their strengths and weaknesses. Based on this analysis, a new DfAM framework is developed, which aims to address the limitations of existing frameworks and provide a comprehensive design approach for additive manufacturing. The second phase of the study involved applying the developed framework to a case study of a complex automotive part - a height adjuster handle. The design requirements of the height adjuster handle were identified based on the principles of DfAM, and the part was designed using computer-aided design (CAD) software and optimised topologically using ANSYS software. In the third phase, the performance of the height adjuster handle designed using the developed framework was compared with a part manufactured with injection moulding technology. The comparison was based on various performance criteria, including mechanical properties, dimensional accuracy, and production time and cost. Findings: The findings of the study demonstrate the effectiveness of the developed design framework for additive manufacturing (DfAM) in producing a complex automotive part with improved performance characteristics and reduced lead time. Research limitations/implications: Although the results of the study provide important insights into the effectiveness of the developed DfAM framework for producing a complex automotive part, there are some limitations to the research that should be considered, such as the case study involved the design of a single part, and the results may not be generalisable to other parts or applications. Further research is needed to validate the effectiveness of the DfAM framework for a broader range of automotive parts. Practical implications: The findings of the study have important practical implications for the automotive industry. The developed DfAM framework can be used in the FDM technology. It can be used as a decision aid in the manufacturing of FDM parts in order to improve the efficiency and cost-effectiveness of the production process for complex automotive parts. Originality/value: The value of the study is the development of a novel DfAM framework and the demonstration of its effectiveness in a case study. The proposed framework can be used as a reference for future research. It can also provide practical guidance for industry professionals seeking to improve the efficiency and cost-effectiveness of their additive manufacturing processes. [ABSTRACT FROM AUTHOR]

Lattice structures in additive manufacturing of 316L stainless steel have gained increasing attention due to their well-suited mechanical properties and lightweight characteristics. Infill structures such as honeycomb, lattice, and gyroid have shown promise in achieving desirable mechanical properties for various applications. However, the design process of these structures is complex and time-consuming. In this study, we propose a machine learning-based approach to optimize the design of honeycomb, lattice, and gyroid infill structures in 316L stainless steel fabricated using laser powder bed fusion (L-PBF) technology under different loading conditions. A dataset of simulated lattice structures with varying geometries, wall thickness, distance, and angle using a computational model that simulates the mechanical behavior of infill structures under different loading conditions was generated. The dataset was then used to train a machine learning model to predict the mechanical properties of infill structures based on their design parameters. Using the trained machine learning model, we then performed a design exploration to identify the optimal infill structure geometry for a given set of mechanical requirements and loading conditions. Finally, we fabricated the optimized infill structures using L-PBF technology and conducted a series of mechanical tests to validate their performance under different loading conditions. Overall, our study demonstrates the potential of machine learning-based approaches for efficient and effective designing of honeycomb, lattice, and gyroid infill structures in 316L stainless steel fabricated using L-PBF technology under different loading conditions. Furthermore, this approach can be used for dynamic loading studies of infill structures. [ABSTRACT FROM AUTHOR]

The main objectives of optimising a mechanical system are to reduce costs and increase performance. Thanks to additive manufacturing, it is possible to exploit shape optimisation to place the material where it is needed. This optimisation implies a gain in material and mass but also changes in mechanical behaviour, for example in the connections. Thus, the boundary conditions on the functional surfaces are different before and after the topological optimisation. The objective of this paper is to show that following a topological optimisation, the functional surfaces (i.e. the non-design spaces) have to be redesigned and/or adapted. For this purpose, it is proposed to study a mechanism using two approaches. The first is the simple optimisation of a mechanism along different optimisation paths. The second approach consists in optimising while considering the inter-linkage efforts. The proposed methodology will be applied on a case study which will demonstrate the impact on the performance with an improvement of the functional surfaces. The result of the study shows that by adapting these non-design spaces, the mechanical strength of the parts is improved with the same gain in mass. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) technologies enable the production of customized and personalized medical devices that facilitate users' comfort and rehabilitation requirements according to their individual conditions. The concept of a tailor-made orthopedic device addresses the accelerated recovery and comfort of the patient through the utilization of personalized rehabilitation equipment. Direct modeling, with an increasing number of approaches and prototypes, has provided many successful results until now. The modeling procedure for 3D-printed orthoses has emerged as the execution of steady and continuous tasks with several design selection criteria, such as cutting, thickening the surface, and engraving the shell of the orthosis. This publication takes into consideration the aforementioned criteria and proposes the creation of a holistic methodology and automated computational design process for the customization of orthotic assistive devices, considering aspects such as material properties, manufacturing limitations, recycling, and patients' requirements. This proposal leads to the designing and manufacturing of a wrist orthopedic device based on reverse engineering, Design for AM (DfAM), and Design for Recycling (DfR) principles. The proposed methodology can be adjusted for different limbs. A dual-material approach was attained utilizing rigid, mechanically enhanced feedstock material and soft elastic material with reduced skin irritation risks to achieve both mechanical requirements and adequate cushioning for user comfort during rehabilitation. Recyclable thermoplastic matrices were selected, which also allow for the option to create washable devices for product life extension. Then, 3D scanning procedures were implemented to acquire the initial anatomic measurements for the design of the WHO and ensure and assess the dimensional accuracy of the final product. Physical mechanical testing was implemented to evaluate the WHO's mechanical behavior and verify its functionality during basic wrist movements. The extracted dimensional data for the two main orthosis components that indicated approximately 50% and 25% of the tolerance values, respectively, were within the range (−0.1 mm, 0.1 mm). [ABSTRACT FROM AUTHOR]

The use of components obtained through the additive manufacturing (AM) technique has become increasingly widespread in recent years, playing a central role in industrial production, and in particular in some fields such as automotive, biomedical, aerospace and electronics. Among all AM techniques, FDM (Fused Deposition Modelling) represents the most used printing technique to produce polymeric and composite components, thanks to the flexible printing process, the low cost and the diversity of the materials adopted. The aim of the present work concerns the comparison between the mechanical properties of three plastic materials printed with the FDM technique (polylactic acid PLA, polyethylene terephthalate glycol-modified PETG and Acrylonitrile-butadiene-styrene ABS) using an Original Prusa i3 MK3S, by varying the raster angle between 0�, 45� and 90� degrees. Infrared Thermography has been adopted to monitor the temperature evolution during static tensile tests and to assess stress level that can initiate damage within the material. Failure analysis was performed to correlate the mechanical behaviour with the microstructural characteristics of the materials

Additive manufacturing has seen remarkable growth in recent years and a rising evolution of industrial applications for direct manufacturing. Many industries are looking to adopt this technology to take advantage of its benefits, such as design freedom and component mass reduction. However, design teams need to gain the experience, training, and design knowledge that allow them to consider the capabilities of this new technology. Existing design methodologies for additive manufacturing only consider a subset of the design process. Most research studies focus on either design heuristics, or design principles, or design rules, and do not provide a structuring and comprehensive design methodology tailored to additive manufacturing. This paper aims to provide designers and companies with a systematic and creative integrated design methodology in a user-centered approach. The benefits and constraints of AM are structured for greater understanding, through the design heuristics, principles, and design rules related to the process. Furthermore, we integrate visualization and prototyping throughout the process to ensure product quality and user fidelity. Hence, this study aims to provide a new methodology for product design for AM that covers the entire process, from the requirement to production. The proposed user-centered methodology integrates the different stakeholders, throughout the project life cycle. Finally, we evaluate the proposed methodology by designing a left-handed mouse as a case study. Novice designers for new product development with AM can also use this solution. [ABSTRACT FROM AUTHOR]

Extensive research on nature-inspired cellular metamaterials has globally inspired innovations using single material and limited multifunctionality. Additive manufacturing (AM) of intricate geometries using multi-materials provides additional functionality, environmental adaptation, and improved mechanical properties. Recently, several studies have been conducted on multi-material additive manufacturing (MMAM) technologies, including multi-materials, methodologies, design, and optimization. However, in the past six years, very few or no systematic and complete reviews have been conducted in this research domain. This review intends to comprehensively summarize MMAM systems and the working principles of its fundamental processes. Herein, the Multi-material combinations and their design, modeling, and analysis strategies have been reviewed systematically. In particular, the focus is on applications and opportunities for using MMAM for several industries and postprocessing MMAM fabricated parts. Furthermore, this review identified the limitations and challenges of existing software packages, MMAM processes, materials, and joining mechanisms, especially at the multi-material interfaces. Finally, we discuss the possible strategies to overcome the aforementioned technological challenges and state the future directions, which will provide insights to researchers and engineers designing and manufacturing complex nature-inspired objects.

The use of components obtained through the additive manufacturing (AM) technique has become increasingly widespread in recent years, playing a central role in industrial production, and in particular in some fields such as automotive, biomedical, aerospace and electronics. Among all AM techniques, FDM (Fused Deposition Modelling) represents the most used printing technique to produce polymeric and composite components, thanks to the flexible printing process, the low cost and the diversity of the materials adopted. The aim of the present work concerns the comparison between the mechanical properties of three plastic materials printed with the FDM technique (polylactic acid PLA, polyethylene terephthalate glycol-modified PETG and Acrylonitrile-butadiene-styrene ABS) using an Original Prusa i3 MK3S, by varying the raster angle between 0°, 45° and 90° degrees. Infrared Thermography has been adopted to monitor the temperature evolution during static tensile tests and to assess stress level that can initiate damage within the material. Failure analysis was performed to correlate the mechanical behaviour with the microstructural characteristics of the materials. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) is proving to be a promising new and economical technique for the manufacture of metal parts. This technique basically consists of depositing material in a more or less precise way until a solid is built. This stage of material deposition allows the acquisition of a part with a quasi-final geometry (considered a Near Net Shape process) with a very high raw material utilization rate. There is a wide variety of different manufacturing techniques for the production of components in metallic materials. Although significant research work has been carried out in recent years, resulting in the wide dissemination of results and presentation of reviews on the subject, this paper seeks to cover the applications of symmetry, and its techniques and principles, to the additive manufacturing of metals. [ABSTRACT FROM AUTHOR]

Design for additive manufacturing (DfAM) enables the design and fabrication of intricate but application-based functionally optimized geometries by reducing the manufacturing time. It also gave unlimited design freedom to alter any specific parameter and regenerate the design with improved mechanical properties. However, designing a complex and application-specific component needs comprehensive knowledge of drawing, intended usage, high expertise, and command of designing software with ample time. Mechanical springs, e.g., wave springs of uniform/complex shaped designs, consume a significant amount of manual hard work. A new design tool, WSdesign, is developed for constructing wave springs of different morphologies with uniform or varying design parameters or a combination of both. A graphical user interface (GUI) was developed in which the user can select the type of wave spring, which can be either uniform, functional gradient, or hybrid with parametric variation defined through Python code. The code is directly run in Autodesk Fusion 360 software which is used to transform that code into a 3D model with all defined features and can be saved in different formats or can be directly printed. Two designs, i.e., rectangular and variable thickness wave springs, were designed each using WSdesign and SolidWorks (manual method), manufactured, and analyzed by performing uniaxial compression testing. The results were compared with each other which were further validated by finite element analysis and found that both design strategies have negligible variations. Furthermore, several designs of complex-shaped wave springs were successfully designed and manufactured using fused deposition modeling (FDM), stereolithography (SLA), and powder bed fusion (MJF) technology with different materials, resulting in a good surface finish, smooth printability, and less dimensional variation, which proves the versatility of WSdesign. In addition, this methodology also enables to design of application-based wave springs for research and industrial usage as per load requirements without having in-depth design expertise and spending much less time. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) is a promising manufacturing technology; it has great manufacturing capabilities and large material diversity, making it applicable for many applications. However, the limited information related to AM processes, materials, and rules restricts its potential popularity over traditional manufacturing methods. For a particular application, the choice of available AM process/machine and material is critical to the application's quality, mechanical properties, and other important factors. Moreover, the large number of AM processes/machines and materials and the overlap among them in terms of capability and functionality further complicate the selection task. AM service selection as a problem has three essential aspects, and all support systems that are built to help users select the optimal AM service must consider these aspects during the system development stage. These aspects are the AM resource capability information source, user intervention, and the methodology suggesting the best AM resources that meet user requirements. These aspects actually represent AM resource definition accuracy and availability, selection system usability, and reliability. This study analyses the essence of these three aspects, reviews the literature, and develops a new AM selection system framework that enhances system functionality regarding these aspects. First, 3D printing service providers in the proposed system are considered the source of AM resource capability information to expand AM service options to users, provide accurate resource definitions, and ensure their availability. Second, the proposed system applied the posteriori-based multicriteria decision-making approach through the integration of decision making trial and evaluation laboratory (DEMATEL), analytic hierarchy process (AHP), and modified Technique for Order Preference by Similarities to Ideal Solution (TOPSIS) techniques. This greatly minimizes user inputs during AM service selection process, fully supports the DFAM (Design for additive manufacturing) concept, and maintains the accuracy of final selection decisions. [ABSTRACT FROM AUTHOR]

Additive Manufacturing (AM) is often considered to increase opportunities for creativity in design compared to traditional manufacturing methods. At the same time, it is suggested that regulated work can have a negative effect on engineers' creative abilities, which are linked to three components of creativity (expertise, motivation, and creative thinking skills). Due to the 'newness' of AM, engineers need to broaden their expertise to fully exploit their creative potential while using AM. Previous research has presented support tools to assist engineers to understand the complexity of AM. A majority of such studies focus on novice engineers, rather than providing an understanding of how AM is involved in industrial practices. This paper follows three case studies from the space industry, a regulated industry, that aims to re-design a product for AM over a 21-month time period. The purpose is to explore how restrictions affect engineers' opportunities to build AM expertise for creativity in a regulated industry. Results show the importance that case-specific aspects have on an engineer's learning path for adopting AM. Engineers find themselves in a complex situation, with a conflict between being 'safe' or innovative, where innovation within such regulated industries is often compared to innovating 'in a box'. [ABSTRACT FROM AUTHOR]

Brackets are the load-bearing components in a satellite. The current age of satellites comprises specific brackets that set out as a link between the bodies of the satellite, reflector parts, and feeder facilities mounted at its upper end. Brackets are used to carry loads of the satellite body frame, supporting elements, batteries, and electronic goods. The article explicates the various brackets used in satellites and aircrafts. The strength of the bracket is of utmost importance since it is an important load supporting member in several assemblies of aircraft and satellites. In addition to the mechanical strength, the weight of the bracket is a major concern as it adds to the total weight of the aircraft and satellite. Thus, weight savings of brackets can be of paramount importance and Additive Manufacturing (AM) is found as an overall solution to achieve the same. Hence, in addition to various brackets used in satellites, the article presents an exhaustive review of the processing of various advanced functional materials using various AM techniques to make high strength-to-weight ratio satellite brackets. The use of DFAM by various satellite manufacturers globally for optimizing the structure of the brackets resulting in a significant weight saving of the brackets is also presented in the article. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) has emerged as a promising technology to cater to the increasing demand for the fabrication of multi-functional, multi-material, and complex parts. AM is revolutionizing production and product development in the aerospace, automotive, and medical fields. However, mismatch in material properties, pervasive imperfections in the printed part, and lack of build consistency are crucial concerns. Higher accuracy in AM processes primarily depends on controlling various aspects of the process. In the last few years, machine learning, data analytics, and design for additive manufacturing have been the most extensively used techniques to address the vital concerns of additive manufacturing. Despite well-known techniques, very few studies reported applications of these techniques for aerospace. Specifically, this study comprehensively reviews recent advancements in the design for additive manufacturing (DfAM) and applications of machine learning and big data analytics to address the prime concerns of AM. The DfAM emphasizes issues and opportunities for topology optimization and methods for generative design for weight reduction and manufacturing of products with high resolution. Simulation and modeling techniques that are being used to improve geometric quality and process analysis are discussed to enable its potential for different applications. Further, automation of AM process using the Internet of things and knowledge-based systematic process planning is discussed to address key issues in process planning of multiple parts. Finally, the current challenges and scope for algorithmically driven AM processes are summarized with the trends of automation in AM to ensure greater efficiency and a better lifecycle of AM products in the era of industry 4.0. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM)—layer-by-layer printing—completely changes the conventional manufacturing method. The design freedom for mirrors is increased without the limits of the manufacturing process. Advanced lightweight mirrors (ALM), new-type mirrors designed using the generative method and lattice technologies, have emerged as the times require. Contrasting with conventional lightweight mirrors (CLM), the performances of ALM are drastically improved. This paper took the Voronoi mirrors as an ALM case study and introduced a design flow. In addition, a conventional honeycomb mirror was designed using the analytical method as the control. The optomechanical performances of the two were further compared through finite element analysis (FEA). Finally, ALM's optomechanical performances outperformed CLM's, including the area density, structural stiffness, surface stability, and quilting deflection. [ABSTRACT FROM AUTHOR]

The design of parts in such critical sectors as the manufacturing of aeronautical parts is awaiting a paradigm shift due to the introduction of additive manufacturing technologies. The manufacture of parts designed by means of the design-oriented additive manufacturing methodology (DfAM) has acquired great relevance in recent years. One of the major gaps in the application of these technologies is the lack of studies on the mechanical behavior of parts manufactured using this methodology. This paper focuses on the manufacture of a turret for the clamping of parts for the aeronautical industry. The design of the lightened turret by means of geometry optimization, the manufacture of the turret in polylactic acid (PLA) and 5XXX series aluminum alloy by means of Wire Arc Additive Manufacturing (WAAM) technology and the analysis by means of finite element analysis (FEA) with its validation by means of a tensile test are presented. The behavior of the part manufactured with both materials is compared. The conclusion allows to establish which are the limitations of the part manufactured in PLA for its orientation to the final application, whose advantages are its lower weight and cost. This paper is novel as it presents a holistic view that covers the process in an integrated way from the design and manufacture to the behaviour of the component in use. [ABSTRACT FROM AUTHOR]

The geometrical constraints and dimensional tolerances lead to specific design issues of MEMS manipulators for biological applications. The target properties become even more important in the case of in vitro manipulation of cells. Several design solutions have been proposed in the literature, however, some issues related to the thermal heating of microgripper tips and to the electric voltage effects still remain unsolved. This paper reports the design for additive manufacturing (DFAM) of micro-electro mechanical systems (MEMS) microgrippers. The design limitations imposed by the micro-stereolithography fabrication process are considered. The design solution proposed in this study is based on compliant structures and external actuation; this layout provides the potential elimination of the main issues related to cells micro-manipulators represented by the excessive thermal heating and the voltage exposure of samples. The simulation through finite elements method (FEM) models of the structure in terms of force–displacement relation and stress distribution supports the design evolution proposed. [ABSTRACT FROM AUTHOR]

This paper evaluates and demonstrates the methods for additively manufactured stent and the use of material ASTM F75 Cobalt-based superalloy (CoCrMo) by evaluating the chemical content, hot isostatic pressing process, mechanical properties, and electrochemical polishing. The commercialise stent available had cause issues in the like of unmatch fitting in the blood vessel, with highly dependent on surgeon guessing during angioplasty; thus, the risk of restenosis or thrombosis can occur. By SLM technique, it creates complex products with high geometric accuracy while allowing the design freedom to produce patient-specific stent. The heat treatment for additively manufactured stent has been done through a series of Hot Isostatic Pressing (HIPing) cycle 1200°C and 14,150 PSI. The sample preparation by chemical etching method was delivered to assess the effect of as-built sample and HIPing where it showed the change pattern of the microstructure. The chemical composition has been assessed by Energy-Dispersive X-ray spectroscopy (EDX) and showed the presence of element Cobalt, Chromium, Molybdenum, and Carbon content. The compressive, flexural, and hardness testing has been conducted to determine the behaviour for an as-built sample and HIPing where the stiffness is drastically improved by 10%. [ABSTRACT FROM AUTHOR]