Potential and challenges of additive manufacturing for topology optimized spacecraft structures

Comparative study on life cycle assessment of components produced by additive and conventional manufacturing process

Design for additive manufacturing (DFAM) seeks to develop designs that take advantage of the unique capabilities of additive manufacturing (AM) processes to maximize benefits. In this paper, several issues at the frontier of DFAM research are highlighted. First, the need is described to include as-manufactured mechanical and other physical properties, such as topology and shape optimization and generative design, during computational design. AM processes rarely produce parts with homogeneous composition and isotropic properties, so design methods and tools should not assume them. Second, the topic of designing for the AM process chain is important since AM-fabricated parts typically need postprocessing operations, such as support removal, finish machining, heat treatments, etc. DFAM methods need to incorporate the entire process chain, not just the AM process, which is explored with an example from metal powder bed fusion. Third, potentially, the largest benefit of AM can be realized by radically rethinking product architectures. Examples of an electric motorcycle and an assistive exosuit illustrate the ideas and potential benefits. Finally, some thoughts on design for 4D printing are offered, specifically for 3D printed morphing and deployable systems that utilize the shape memory effect.

Recently, additive manufacturing (AM) has been a useful technology to fabricate complex parts. However, more consideration and technological developments are required for the expansion of the AM process in various industries. In particular, verification for repeatability and reproducibility of AM parts are very difficult issues when the AM parts are used in specific industries, such as nuclear and aerospace. In this respect, the change in the mechanical properties according to the relationship between AM parameters, machines, and powders is a very important area of research. In this study, four different L-PBF machines and three different powders from different suppliers were used to fabricate stainless steel 316L AM materials using same or similar AM parameters. In addition, tensile tests were conducted on all AM materials to obtain mechanical properties. The test results confirmed that differences in the mechanical properties were observed in the same AM process parameters of different machines and powder conditions.

Additive manufacturing (AM) has recently been accorded considerable interest by manufacturers. Many manufacturing industries, amongst others in the aerospace sector, are already using AM parts or are investing in such manufacturing methods. Important material properties, such as microstructures, residual stress, and surface topography, can be affected by AM processes. In addition, a subtractive manufacturing (SM) process, such as machining, is required for finishing certain parts when accurate tolerances are required. This finish machining will subsequently affect the surface integrity and topography of the material. In this research work, we focused on the surface integrity of Ti-6Al-4V parts manufactured using three different types of AM and finished using an SM step. The aim of this study was to gain an understanding on how each process affects the resulting surface integrity of the material. It was found that each AM process affects the materials’ properties differently and that clear differences exist compared to a reference material manufactured using conventional methods. The newly generated surface was investigated after the SM step and each combination of AM/SM resulted in differences in surface integrity. It was found that different AM processes result in different microstructures which in turn affect surface integrity after the SM process.

PurposeThe purpose of this paper is to communicate a method to perform simultaneous topology optimization of component and support structures considering typical metal additive manufacturing (AM) restrictions and post-print machining requirements.Design/methodology/approachAn integrated topology optimization is proposed using two density fields: one describing the design and another defining the support layout. Using a simplified AM process model, critical overhang angle restrictions are imposed on the design. Through additional load cases and constraints, sufficient stiffness against subtractive machining loads is enforced. In addition, a way to handle non-design regions in an AM setting is introduced.FindingsThe proposed approach is found to be effective in producing printable optimized geometries with adequate stiffness against machining loads. It is shown that post-machining requirements can affect optimal support structure layout.Research limitations/implicationsThis study uses a simplified AM process model based on geometrical characteristics. A challenge remains to integrate more detailed physical AM process models to have direct control of stress, distortion and overheating.Practical implicationsThe presented method can accelerate and enhance the design of high performance parts for AM. The consideration of post-print aspects is expected to reduce the need for design adjustments after optimization.Originality/valueThe developed method is the first to combine AM printability and machining loads in a single topology optimization process. The formulation is general and can be applied to a wide range of performance and manufacturability requirements.

PurposeThis paper aims to present a systematic approach in the literature survey related to metal additive manufacturing (AM) processes and its multi-physics continuum modelling approach for its better understanding.Design/methodology/approachA systematic review of the literature available in the area of continuum modelling practices adopted for the powder bed fusion (PBF) AM processes for the deposition of powder layer over the substrate along with quantification of residual stress and distortion. Discrete element method (DEM) and finite element method (FEM) approaches have been reviewed for the deposition of powder layer and thermo-mechanical modelling, respectively. Further, thermo-mechanical modelling adopted for the PBF AM process have been discussed in detail with its constituents. Finally, on the basis of prediction through thermo-mechanical models and experimental validation, distortion mitigation/minimisation techniques applied in PBF AM processes have been reviewed to provide a future direction in the field.FindingsThe findings of this paper are the future directions for the implementation and modification of the continuum modelling approaches applied to PBF AM processes. On the basis of the extensive review in the domain, gaps are recommended for future work for the betterment of modelling approach.Research limitations/implicationsThis paper is limited to review only the modelling approach adopted by the PBF AM processes, i.e. modelling techniques (DEM approach) used for the deposition of powder layer and macro-models at process scale for the prediction of residual stress and distortion in the component. Modelling of microstructure and grain growth has not been included in this paper.Originality/valueThis paper presents an extensive review of the FEM approach adopted for the prediction of residual stress and distortion in the PBF AM processes which sets the platform for the development of distortion mitigation techniques. An extensive review of distortion mitigation techniques has been presented in the last section of the paper, which has not been reviewed yet.

Recently, Additive Manufacturing (AM) has been widely used in many applications. For a particular AM component, the choice of available AM processes is critical to the component’s quality, mechanical properties, and other important factors. In that context, this article presents an efficient decision support system for the selection of an appropriate AM process. A novel hybrid Multi-Criteria Decision Making (MCDM) technique has been proposed to select an appropriate AM process from available AM processes. The Best Worst Method (BWM) is used to determine optimal weights of criteria and the Proximity Indexed Value (PIV) method is employed to rank the available AM processes. For benchmarking the abilities of an AM process, a conceptual model of spur gear was fabricated by four available AM processes viz., Vat Photopolymerization (VatPP), Material Extrusion (ME), Powder Bed Fusion (PBF), and Material Jetting (MJ). Additionally, Dimensional accuracy (A), surface roughness (R), tensile strength (S), percentage elongation (%E), heat deflection temperature (HDT), process cost (PC) and build time (BT) has been considered as most significant criteria. Further, sensitivity analysis has been performed to validate the reliability of the results. The results suggested that the Material Jetting (MJ) process produces dimensionally accurate and quality parts among available alternatives AM processes. The ranking obtained using the PIV method is consistent and reliable.

Additive manufacturing (AM) is a cutting‐edge technique for constructing intricate components with unique microstructural features and strength comparable to wrought alloys. Due to their exceptional corrosion resistance and mechanical properties, duplex stainless steels (DSS) are used in a wide range of critical applications. Over the past several years, a substantial body of research has been conducted on the AM of DSS. In‐depth knowledge is required to understand the complete benefits of the AM process. This review overviews the AM‐processed DSS parts based on process‐specific microstructural changes, mechanical behavior, electrochemical performance, and postheat treatment processes based on the classifications of directed energy deposition and powder bed fusion AM techniques along with future perspectives. Major challenges in AM of DSS are optimizing the austenite–ferrite fractions and controlling the formations of deleterious phases. This review will be extensively useful to researchers and industries working in the AM of DSS.

Purpose This paper studies the feasibility of additive manufacturing (AM) processes and their potential materials to produce mold inserts for injection molding (IM) of plastic parts. This study aims to describe the technological advancements and practical implications of integrating AM with IM to produce plastic parts, reducing the gap and determining the feasibility of AM for insert production. Design/methodology/approach A literature search of different databases was done. Applying the PRISMA methodology, the 67 most relevant articles between 2013 and 2024 were selected. From these, a bibliometric analysis was performed, and the main results regarding the mechanical properties and the number of injection cycles achieved by inserts were extracted. Findings Material jetting (MJT), vat photopolymerization via ultraviolet light laser (VPP-UVL) and laser powder bed fusion using metal powders (PBF-LB/M) are the most useful AM processes reported in the literature to produce inserts for IM. Studies show that the maximum number of successful injection cycles achieved with these AM inserts has been 116, 85 and more than 500 cycles, respectively. The molded geometry, the injected material and the IM parameters influence the number of injection cycles, being the injection pressure, the mold temperature and the injection temperature the most critical parameters to consider in extending the life of the inserts. Originality/value To the best of the authors’ knowledge, this study provides the first systematic review with a comprehensive overview of this innovative approach to evaluate the emerging directions, current barriers and future potential of using AM with IM to manufacture plastic parts. As such, this study highlights the primary findings in the literature concerning AM processes and the materials commonly used to manufacture inserts for IM.

Effect of process parameters on mechanical properties of additively manufactured metallic systems

PurposeMaterial extrusion (MEX) is a class of additive manufacturing (AM) process based on MEX principle. In the viewpoint of Industry 4.0 and sustainable manufacturing, AM technologies are gaining importance than conventional manufacturing route (subtractive manufacturing). Because of the ease of use and lesser operation skills, MEX had wide popularity in industry for product and prototype development. This study aims to analyze energy consumption of MEX-based AM process and its influencing factors.Design/methodology/approachA group of factors were identified pertaining to MEX-based AM process. In this viewpoint, this study presents the configuration of a structural model using interpretive structural modeling (ISM) to depict dominant factors in MEX-based AM process. A total of 18 influencing factors are identified and ranked using ISM methodology for MEX process. The Impact Matrix Cross-reference Multiplication Applied to a Classification analysis was done to categorize influencing factors into four groups for MEX-based AM process.FindingsThe derivation of structural model would enable AM practitioners to systematically analyze the factors and to derive key factors which enable comprehensive energy modeling and energy assessment studies. Also, it facilitates the development of energy efficient AM system.Originality/valueThe development of structural model for analysis of factors influencing energy consumption of MEX-based AM is the original contribution of the authors.

PurposeDue to the complexity of and variations in additive manufacturing (AM) processes, there is a level of uncertainty that creates critical issues in quality assurance (QA), which must be addressed by time-consuming and cost-intensive tasks. This deteriorates the process repeatability, reliability and part reproducibility. So far, many AM efforts have been performed in an isolated and scattered way over several decades. In this paper, a systematically integrated holistic view is proposed to achieve QA for AM.Design/methodology/approachA systematically integrated view is presented to ensure the predefined part properties before/during/after the AM process. It consists of four stages, namely, QA plan, prospective validation, concurrent validation and retrospective validation. As a foundation for QA planning, a functional workflow and the required information flows are proposed by using functional design models: Icam DEFinition for Function Modeling.FindingsThe functional design model of the QA plan provides the systematically integrated view that can be the basis for inspection of AM processes for the repeatability and qualification of AM parts for reproducibility.Research limitations/implicationsA powder bed fusion process was used to validate the feasibility of this QA plan. Feasibility was demonstrated under many assumptions; real validation is not included in this study.Social implicationsThis study provides an innovative and transformative methodology that can lead to greater productivity and improved quality of AM parts across industries. Furthermore, the QA guidelines and functional design models provide the foundation for the development of a QA architecture and management system.Originality/valueThis systematically integrated view and the corresponding QA plan can pose fundamental questions to the AM community and initiate new research efforts in the in-situ digital inspection of AM processes and parts.

Additive manufacturing (AM) of metals have become a promising fabrication method, due to the decreased waste from conventional manufacturing and the ability to create complex geometries [1]. However, the surface roughness of powder based additively manufactured structures appears porous, with complicated geometries that are a concern for localized corrosion. Knowing which defects are more susceptible than others, from a geometry perspective, will greatly aid mitigation strategies either in terms of AM process parameters or through post-build surface treatments. This study will explore how surface defects created on AM stainless steel parts impact local corrosion stability under atmospheric conditions.The stochastic nature of the pits initiating and repassivating, combined with the complexities of the AM defects and those of thin water layers, make for a very large parameter space to explore. In effect, the most important aspect of localized corrosion under these conditions is the determination of whether a pit will repassivate or grow, and if it grows, how large can it become. Many different parameters affect the pit stability, including the geometry of the cathode size, the anode (pit) size, details of the environment (solution composition, electrochemical potential), and the water layer thickness.It is known that the potential at a pit mouth must be more positive than in order to grow stably [2]. The repassivation potential therefore serves as one way to measure pit stability, while other parameters in the system are held constant. An additional pit stability criteria is the pit stability product, (i ⋅ x), from Galvele’s seminal work [3]. The maximum pit model [4] uses these criteria, parameters that define the thin electrolyte, and the current-potential relationship for the cathodic reaction(s) on the external surface to define the largest hemispherical pit for which the Conservation of Charge is met.Finite element modeling is used here to determine what combinations of geometric parameters associated with surface defects due to AM processing of SS316 lead to the stabilization of a pit or not. Pits of different dimensions, including hemispherical, rectangle, and disk shaped, are assessed as isolated pits. The model’s geometric complexity is then increased to better represent an additively manufactured surface with many pits of different shapes and sizes based on cross-sectional data from actual surfaces. A range of atmospheric conditions are investigated, including a range of relative humidity and salt loading density. The boundary conditions within the model represent the solution kinetics of both scenarios. The water layer and loading densities were varied, according to the equation proposed by Chen et al. [5].SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525. SAND2020-5408 A.[1] B. AlMangour and J. M. Yang, “Improving the surface quality and mechanical properties by shot-peening of 17-4 stainless steel fabricated by additive manufacturing,” Mater. Des., vol. 110, pp. 914–924, 2016.[2] J. Srinivasan, M. J. McGrath, and R. G. Kelly, “A High-Throughput Artificial Pit Technique to Measure Kinetic Parameters for Pitting Stability,” J. Electrochem. Soc., vol. 162, no. 14, pp. C725–C731, 2015.[3] J. R. Galvele, “Transport Processes and the Mechanism of Pitting of Metals,” J. Electrochem. Soc., vol. 123, no. 4, p. 464, 1976.[4] R. M. Katona, J. Carpenter, E. J. Schindelholz, and R. G. Kelly, “Prediction of Maximum Pit Sizes in Elevated Chloride Concentrations and Temperatures,” J. Electrochem. Soc., vol. 166, no. 11, pp. C3364–C3375, 2019.[5] Z. Y. Chen, F. Cui, and R. G. Kelly, “Calculations of the Cathodic Current Delivery Capacity and Stability of Crevice Corrosion under Atmospheric Environments,” J. Electrochem. Soc., pp. 360–368, 2008.

Additive manufacturing (AM) has gained notoriety for offering advantages over traditional manufacturing methods, such as increased design complexity and flexibility. However, it has not found widespread use beyond rapid prototyping. One hindrance to the acceptance of AM processes in industry is the time and cost of fabrication per component. While metal AM by itself can be inexpensive, extra manufacturing steps in the form of subtractive manufacturing (SM) may need to be performed to reach final part tolerances, leading to hybrid additive-subtractive manufacturing (HASM) of a part, which increases time and cost. A potential area to reduce cost is through increasing the efficiency of the HASM process by conducting additive and subtractive manufacturing simultaneously. Usually, HASM is performed in a process where AM is completed in one machine or cell and transferred to another machine or cell for SM in a sequential assembly line process. This efficiency decreases part cost, but high aspect ratio parts or parts with internal geometry that require interleaved additive deposition and machining cannot be produced. One unexplored solution to simultaneous HASM that allows for interleaved operations is to operate the deposition head and machining spindle concurrently within the same machine envelope, known as concurrent HASM (CHASM). In this type of process, both AM and SM occur simultaneously on a batch of small parts or a single large part, maintaining a high efficiency without sacrificing the full range of complex geometries that AM allows for. A potential approach to the single-machine method could be to combine a robot and mill within the same envelope. A challenge to this approach, however, is control of both systems. Most machine controllers have limited external communication or, if a robot has been integrated, only offer movement of either the robot or mill at any given time. As a result, systems must pause either the AM or SM process to switch between them rather than working simultaneously. The present work investigates the positional accuracy of such a CHASM system comprised of a robotic arm and a 3-axis mill. Open-loop tests with limited communication between machines are performed on the system to verify positional error during concurrent robot-mill movements. Under certain conditions, it is demonstrated that position error can stay within 2 mm for the duration of a single layer; however, these tests show that, generally, the open-loop positioning performance of the system is inadequate for CHASM without part-specific hand-tuning of parameters. Based on these results, a set of requirements for successful robot-CNC CHASM is proposed for future integrations.

The advance in computational science and engineering allows people to simulate the additive manufacturing (AM) process at high fidelity, which has turned out to be a valid way to model, predict, and even design the AM processes. In this paper, we propose a new method to simulate the melting process of metal powder-based AM. The governing physics is described using partial differential equations for heat transfer and Laminar flow. Level set methods are applied to track the free surface motion of the molten metal flow. Some fundamental issues in the metal-based AM process, including free surface evolution, phase transitions, and velocity field calculation, are explored, which help us gain insight into the metal-based AM process. The convergence problem is also examined to improve the efficiency in solving this multiphysics problem.