Design For Additive Manufacturing Research Articles

Structural and thermal generative design using reinforcement learning-based search strategy for additive manufacturing

This paper proposes a reinforcement learning-based topology optimization (TO)/generative design approach using the Upper Confidence Bound (UCB) method to achieve a diverse set of optimal part designs for additive manufacturing. The UCB method has been integrated into two density-based TO problems – a compliance minimization problem and a thermal conduction problem along with Design for Additive Manufacturing (DfAM) filters to ensure improved additive manufacturability of the resultant topologies using different AM processes. The DfAM constraints are enforced by applying the support minimization filter and the thin feature minimization constraint in the TO model. The Solid Isotropic Material Penalization based TO model is perturbed to various levels of exploration and exploitation using the UCB exploration parameter to present different optimal designs. Unlike other data-reliant deep learning methods used in TO, the non-data-driven learning method proposed in this research is based on historical TO iterations integrated into a DfAM-constrained TO model, and it improves the method’s scalability to real-world and often computationally expensive part design applications. This paper fulfills a gap in computationally efficient methods for exploring generative designs of structural and thermal loaded parts with improved functional performance and additive manufacturability.

Design for additive manufacturing for prediction of deformations and residual stresses on topologically optimised structure

The flexibility offered by additive manufacturing (AM) to manufacture complex geometries has strengthened the production of topologically optimised parts following functional requirements. Production of these complex topologically optimised geometries through AM is not devoid of defects. Design for AM must address this issue, especially the deformation and residual stress generated during the part build, which is common in almost all the existing AM processes. This paper proposes a methodology to optimise the shape of the part and then use the systematically planned experiments to find the optimum process setting to minimise the studied defects. A three-dimensional mathematical model was developed and topologically optimised using the finite element method. The AM process simulation used the optimised structure to predict the structure's deformation and residual stress distribution. The study helps minimise the occurrence of studied defects and provides insight into their occurrence and regions which may be predominantly affected by these defects.

Personalized Wearable Ankle Robot Using Modular Additive Manufacturing Design

Personalized Wearable Ankle Robot Using Modular Additive Manufacturing Design

Break it down: comparing the effects of lecture- and module-style design for additive manufacturing educational interventions on student designers’ learning and creativity

ABSTRACT The growing presence of additive manufacturing (AM) in engineering has resulted in a consequent need for AM and design for AM (DfAM) educational interventions in design. Several researchers have proposed AM and DfAM educational interventions; however, some argue that these efforts might not be sufficient to develop higher-level skills (e.g., leveraging AM capabilities for creative design). Prior work suggests that longer, spaced educational interventions are more effective in encouraging learning and information retention; however, these interventions could also be time-consuming and expensive to implement. Our aim in this research is to compare two variations of a DfAM educational intervention: (1) a module-style intervention spread over two sessions with the introduction of DfAM evaluation metrics, and (2) a lecture-style intervention completed in a single session with no evaluation metrics introduced. From our results, we see that students from the module-style intervention reported a greater increase in their DfAM self-efficacy and reported having given a greater emphasis on part consolidation and feature size. However, the structure of the educational intervention did not influence the creativity of ideas generated by the students. These findings highlight the utility of module-style DfAM educational interventions toward increasing DfAM self-efficacy, but not necessarily design creativity.

An Integrative Computational Design Workflow and Validation Methodology for 3D-Printed Personalized Orthopedic Devices: Case Study of a Wrist–Hand Orthosis (WHO)

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).

Non-parametric optimization for lightweight and high heat conductive structures under convection using metaheuristic structure binary-distribution method

In this paper, we propose a novel Metaheuristic Structure Binary-Distribution (MSB) method for attaining lightweight and high thermal conductive structure. MSB combines metaheuristic search with gradient descent optimization, offering a robust and efficient approach. The paper also introduces a connectivity filtering approach to enhance additive manufacturability and eliminate segregated materials in thermal structures, improving integrity and minimizing materials wastage. The performance of the MSB method is compared to other topology optimization methods, namely bi-directional evolutionary structural optimization (BESO), solid isotropic materials with penalization (SIMP), and the parametrized level set method (PLSM). Results consistently demonstrate the better performance of MSB in weight reduction and minimizing thermal compliance. Even at significant weight reductions (50%, 60%, and 70%), MSB outperforms other methods, achieving lower thermal compliance. Investigations on mesh impact and the effectiveness of MSB with suggested connectivity filtering show a successful reduction of islands to solid elements to 0%, improving additive manufacturability and decreasing thermal compliance. The feasibility and suitability of the optimized designs for additive manufacturing are validated through 3D printing, confirming the practicality of the MSB method.

A new gradient infill design method for material extrusion using density-based topology optimization and G-code extension

Gradient infill design (GID) is important in design for additive manufacturing (AM) because it can improve the strength of filled structures. Conventional GID methods aim at product design and use mathematics to formulate the infill geometry; thus, they are complex and require a high level of expertise from the designer. In this work, we propose a GID approach targeting the process planning phase, where density information from topology optimization is used to extend the G-code for printing a part. To verify the advantages of this method, we programmed an algorithm to extend G-code, produced samples, and performed displacement-force bending tests.

Design for Additive Manufacturing: Recent Innovations and Future Directions

Design for additive manufacturing (DfAM) provides a necessary framework for using novel additive manufacturing (AM) technologies for engineering innovations. Recent AM advances include shaping nickel-based superalloys for lightweight aerospace applications, reducing environmental impacts with large-scale concrete printing, and personalizing food and medical devices for improved health. Although many new capabilities are enabled by AM, design advances are necessary to ensure the technology reaches its full potential. Here, DfAM research is reviewed in the context of Fabrication, Generation, and Assessment phases that bridge the gap between AM capabilities and design innovations. Materials, processes, and constraints are considered during fabrication steps to understand AM capabilities for building systems with specified properties and functions. Design generation steps include conceptualization, configuration, and optimization to drive the creation of high-performance AM designs. Assessment steps are necessary for validating, testing, and modeling systems for future iterations and improvements. These phases provide context for discussing innovations in aerospace, automotives, construction, food, medicine, and robotics while highlighting future opportunities for design services, bio-inspired design, fabrication robots, and machine learning. Overall, DfAM has positively impacted diverse engineering applications, and further research has great potential for driving new developments in design innovation.

Towards closed-walled designs in topology optimization using selective penalization

3D topology optimization using a density approach with penalization usually produces truss-like, open-walled structures. The coarser the mesh, the smaller the volume fraction, and the faster the penalization is increased, the more pronounced this effect tends to be. However, closed-walled designs are often more efficient and have other beneficial properties. For instance, closed walls can contribute to achieving self-supporting designs for additive manufacturing that potentially require fewer sacrificial support structures than truss-like designs. This paper presents a two-step optimization procedure for generating closed-walled designs using coarse meshes. The first step takes the usual Eulerian approach of performing a SIMP-based topology optimization on a fixed mesh. To keep thin geometrical features, like walls with a thickness below element size, penalization is switched off deliberately where the formation of such features is detected. Adopting a Lagrangian description, intermediate densities still present in the optimized design are subsequently eliminated in a second step by shrinking each element according to its density. By analogy with volumetric thermal contraction, this is accomplished by solving a fictitious thermo-elastic problem where the temperature has been replaced by a density expression. The outcome is a morphed mesh with a somewhat smoothed surface and a volume close to the specified material volume limit. This body-fitted representation of the design considerably simplifies the final conversion into a manufacturable CAD-type geometry. The two-step optimization procedure is applied to a cantilever, a torsion rod, and a disk reinforcement benchmark problem. Optimized designs are closed-walled and show very good agreement to those found for much finer meshes. Problem-specific stiffness improvements over truss-like designs between 6% and almost 30% were achieved and confirmed the findings previously reported by other authors.

FINITE ELEMENT ANALYSIS AND TOPOLOGY OPTIMIZATION OF A HIGH-PERFORMANCE LOWER PROSTHETIC LIMB

Due to the recent development of additive manufacturing technologies, it is now possible to achieve rapid fabrication of fully functional customized products with high geometric complexity and without the constraints of traditional manufacturing techniques, such as machining. In the current paper, a lower prosthetic limb with the knee joint was designed according to the international standards and the recommendations from existing literature. Finite element analyses were performed to investigate the mechanical behavior of the prosthetic limb and detect the stress concentration regions under realistic operation conditions. For this analysis, Nickel alloy 718 was employed as a construction material. The applied loads were derived for a human body weight of 75kg after an extensive literature review. Then, design optimization was applied, employing design for additive manufacturing (DfAM) techniques in order to minimize the number of assembly parts and improve the shape of the object. Moreover, topology optimization processes were performed in order to develop a lightweight prosthetic limb and achieve a mass reduction of 67% compared to the original design. It is worth mentioning that, this remarkable weight reduction was attained without compromising the structural integrity of the part, as the factor of safety was calculated at 1.22.

An Evolutive-Deformation approach to enhance self-supporting areas in Additive Manufacturing designs

Additive Manufacturing (AM) technology has matured rapidly in recent years, opening an engineering design freedom front when combined with Topology Optimization (TO). Although there is no doubt about their potential to provide optimal parts, there still exists a wide gap between them which reduces the efficiency of the design process. Overhang constraints in TO are still limited, therefore the designs generated by these algorithms are not yet ready for being directly manufactured. They usually need support structures to avoid droops or warps, which is time-consuming, costly and can lead to the loss of the optimal path since designers are required to manually redesign the geometry. The proposed approach combines both design and AM constraints into an automatic workflow in which the geometry provided by the TO software is evolved to minimize support structures for any printing direction while preserving its structural performance. The NSGA-II algorithm is coupled with a Free-Form Deformation (FFD) method to develop different geometries, while fitness is evaluated with FEM analysis. The framework provides Pareto Fronts with the most promising printing directions and geometries in terms of support structures, stiffness and weight. This multi-objective optimization approach that aims to improve TO parts manufacturability is applied to two case studies and one real-world part, highlighting on average a reduction of support structures of around 30%, whereas mass is practically preserved and stiffness decreased by 5%.

KNOWLEDGE-DRIVEN DESIGN FOR ADDITIVE MANUFACTURING: A FRAMEWORK FOR DESIGN ADAPTATION

AbstractDue to the high freedom of design, additive manufacturing (AM) is increasingly substituting conventional manufacturing technology in several sectors. However, the knowledge and the awareness for the suitable design of additively manufactured components or assemblies ensuring manufacturability and fully realizing its potential is still lacking. In recent years, approaches and tools have emerged that allow the incorporation of existing knowledge of Design for Additive Manufacturing (DfAM) into the design process. Nevertheless, these applications mostly do not consider the formalisation of both restrictive and opportunistic DfAM guidelines for their integration in design tools.Therefore, the following article presents a framework for the knowledge-driven adaptation of existing designs in the context of DfAM within an expert system. The novelty of the presented approach lies in the interdisciplinarity between the formalization of design guidelines and their integration and consideration within computeraided design for the semi-automated adaptation of functional non-assembly mechanisms. The application of the presented framework to a case study manufactured via Fused Layer Modeling (FLM) illustrates the applicability and benefits.

A DFAM FRAMEWORK FOR THE DESIGN OF COMPLIANT STRUCTURES

AbstractAdditive manufacturing methods present prospects for designed mechanical deformation via the integration of controlled anisotropic lattice structure forms. Their assimilation into a Design for Additive Manufacturing (DfAM) process would create a novel framework for the design of compliant mechanisms (CM). The method uses lattice structures to replace rigid multi-part mechanisms, with integrated and controlled flexibility into a single, compact, and precise component. In recent years, a lot of research has gone into making algorithms that enable users to generate CMs for their designs. But by relying on algorithms to design solutions, are they neglecting to fully understand how these mechanisms work. This work undertakes the design and development of a novel DfAM Framework, that utilises controlled lattice structure deformations to create a standardised method of CM design. The authors have developed a method for this, whilst allowing users to tailor CMs to their design, by using a wide selection of pretested structures. Indicating suitable structures for their design using an integrated novel taxonomy. The framework is tested and developed using a series of case studies.

WORK IN PROGRESS: DEVELOPMENT OF EDUCATIONAL KIT FOR TEACHING ADDITIVE MANUFACTURING

AbstractAdditive Manufacturing (AM) is a unique manufacturing technology that is being rapidly accepted in various industries, leading to increased demand for experts who know to work with AM and how to design AM products. This led to a broader adaptation of AM in an educational context with various research on how to teach AM. However, most approaches are focused on teaching advanced AM application and Design for AM (DfAM), including both restrictive and opportunistic approaches, with little attention to specialised educational tools to show and teach the basic principle, possibilities and characteristics of AM. This paper presents the development of an Educational Kit for AM to address the gap and help teachers to explain the basics of AM, with a current focus on the material extrusion process. The Educational Kit is made of 17 models and accompanied cards explaining the essential characteristics of AM through short textual explanations, graphics, examples and manufacturing data. The Educational Kit for AM is intended to be used in introductory lessons on AM, so the novices in AM can quickly grasp the characteristics of AM and the basic terms used in AM before advancing to other AM and DfAM topics.

SIMULATING BIORESORBABLE LATTICE STRUCTURES TO ENABLE TIME-DEPENDENT STIFFNESS IN FRACTURE FIXATION DEVICES

AbstractAdditive manufacture (AM) enables a greatly increased design freedom owing to its ability to manufacture otherwise difficult or impossible geometries. However, design creativity can often present itself as a barrier to realising the advantages that AM could offer. In this study the use of AM, bioresorbable materials and lattice design is considered as a method of satisfying contradicting design requirements during fracture healing. Often, immediately after a fracture high stiffness fixation is required; contradictingly during the remodelling phase high stiffness can inhibit bone healing. This study proposes the use of a bioresorbable body centred cubic (BCC) or face centred cubic (FCC) lattice structure to meet the need for tailored variation in implant stiffness over time. To reduce computational expense of lattice modelling a method is outlined, including the use of homogenisation. Results show homogenised representations perform within 5.2% and 1.4% for BCC and FCC unit cells respectively, with a 95% reduction in computational expense. Using resorption rates from the literature, time-dependent change in unit cell geometry was also modelled, showing the way in which a decrease in stiffness over time could be achieved.

Experimental and Computational Investigation of Shaped Film Cooling Holes Designed to Minimize Inlet Separation

Abstract Film cooling is used to protect turbine components from the extreme temperatures by ejecting coolant through arrays of holes to create an air buffer from the hot combustion gases. Limitations in traditional machining meant film cooling holes universally have sharp inlets, which create separation regions at the hole entrance. The present study uses experimental and computational data to show that these inlet separation are a major cause of performance variation in crossflow fed film cooling holes. Three-hole designs were experimentally tested by independently varying the coolant velocity ratio (VR) and the coolant channel velocity ratio (VRc) to isolate the effects of crossflow on hole performance. Leveraging additive manufacturing (AM) technologies, the addition of a 0.25D radius fillet to the inlet of a 7-7-7 shaped hole is shown to significantly improve diffuser usage and significantly reduce variation in performance with VRc. A second AM design used a very large radius of curvature inlet to reduce biasing caused by the inlet crossflow. Experiments showed that this “swept” hole design did minimize biasing of the coolant flow to one side of the shaped hole, and it significantly reduced variations due to varying VRc. RANS simulations at six VR and three VRc conditions were made for each geometry to better understand how the new geometries changed the velocity field within the hole. The sharp and rounded inlets were seen to have very similar tangential velocity fields and jet biasing. Both AM inlets created more uniform, slower velocity fields entering the diffuser. The results of this article indicate that large improvements in film cooling performance can be found by leveraging AM technology.

Advances in the Manufacturing Process of Space Maintainers in Pediatric Dentistry: A Systematic Review from Traditional Methods to 3D-Printing

Background: Three-dimensional (3D) printing is an innovative technology widely used in dentistry for manufacturing objects of various shapes using different materials. It has gained increasing popularity in the field of pediatric dentistry, particularly in the production of space maintainers, which serve as a preventive orthodontic treatment following the early loss of primary molars. Aims: In this systematic review, we present a comprehensive overview of the manufacturing process for space maintainers, ranging from traditional procedures to the advancements in 3D printing technology. Materials and Methods: Our review adheres to the PRISMA criteria and includes scientific articles published until 27 May 2023, without any restriction on the publication period and language. To conduct our research, we searched electronic databases, such as Medline, Web of Science, and Embase, using specific keywords and MeSH terms. Results: We identified 9 articles that discussed the CAD/CAM manufacturing and 3D printing of various types of space maintainers. Conclusions: Based on this systematic review, it is evident that 3D-printed space maintainers offer great potential as an alternative to conventionally processed ones, by addressing their limitations. However, further studies are required to evaluate the accuracy, efficacy, and clinical success rates of different 3D printing technologies, materials, and designs for additive manufacturing of space maintainers.

The technology-behavioral compensation effect: Unintended consequences of health technology adoption

In their pursuit of public health goals, policymakers increasingly turn to innovative apps to complement existing health measures. However, findings from previous research in non-IT health contexts indicate that individuals may compensate for new interventions (e.g., start exercising) by reducing existing preventive health behaviors (e.g., eating fewer healthy foods). However, the findings are inconclusive, and it is unknown when people tend to engage in behavioral compensation. Building on this observation, we draw on rational choice theory to substantiate the subjective rationality of compensation behavior and develop a utility maximization model that suggests circumstances under which adoption of technological innovation may lead to users reducing existing preventive health behaviors. This research provides evidence from a multi-wave study on COVID-19 contact-tracing apps that confirms the existence of what we term the technology-behavioral compensation effect: Individuals who perceive the app to be highly useful or actively use it reduce other preventive health behaviors (e.g., social distancing) after app adoption. Ironically, this technology-behavioral compensation effect indicates a hitherto-overlooked tension between two established IS design goals (i.e., perceived usefulness and active use) and the successful exploitation of technology to support users’ health. We expand research on dark side effects of IS use by revealing a previously neglected type of unintended consequence and elaborate on its implications for research well beyond the health context. Our findings also will help policymakers make decisions on the design of societal technologies.

Cells-in-Touch: 3D Printing in Reconstruction and Modelling of Microscopic Biological Geometries for Education and Future Research Applications.

Additive manufacturing (3D printing) and computer-aided design (CAD) still have limited uptake in biomedical and bioengineering research and education, despite the significant potential of these technologies. The utility of organ-scale 3D-printed models of living structures is widely appreciated, while the workflows for microscopy data translation into tactile accessible replicas are not well developed yet. Here, we demonstrate an accessible and reproducible CAD-based methodology for generating 3D-printed scalable models of human cells cultured in vitro and imaged using conventional scanning confocal microscopy with fused deposition modeling (FDM) 3D printing. We termed this technology CiTo-3DP (Cells-in-Touch for 3D Printing). As a proof-of-concept, we created dismountable CiTo-3DP models of human epithelial, mesenchymal, and neural cells by using selectively stained nuclei and cytoskeletal components. We also provide educational and research context for the presented cellular models. In the future, the CiTo-3DP approach can be adapted to different imaging and 3D printing modalities and comprehensively present various cell types, subcellular structures, and extracellular matrices. The resulting CAD and 3D printed models could be used for a broad spectrum of education and research applications.

Design for additive manufacturing: Review and framework proposal

Additive manufacturing (AM) technologies have seen fast growth in the last few decades. AM needs the implementation of new methods in design, fabrication, and delivery to end-users. Hence, AM techniques have given great flexibility to designers as the design of complex components and highly customized products are no longer binding from a manufacturability point of view. In addition to high material variety, this allows multi-material and variable mechanical characteristics of product manufacturing. This review paper addresses the design for additive manufacturing (DfAM) rules, guidelines, and tools to guide the designer to take advantage of the opportunities provided by AM whether in the early design stages (EDS) or in the later phase using computer-aided design (CAD) tools. It discusses issues related to the design for AM and proposes a DfAM framework applied in the design for the additive manufacturing process.