Orientation Optimization in Layer-Based Additive Manufacturing Process

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.

Additive manufacturing (AM) is an advanced manufacturing technology that offers significant advantages for producing complex geometries, but it also presents unique challenges, particularly in managing overhangs and selecting appropriate build orientations. Overhangs, which are unsupported features that extend beyond the main structure, can lead to defects such as warping, sagging, and incomplete fusion during fabrication. To address these challenges, this chapter explores the integration of overhang constraints and build orientation as critical factors in the topology optimization process for AM. The study demonstrates that incorporating overhang constraints into the optimization algorithm can significantly reduce the need for support structures, thereby minimizing material usage, post-processing requirements, and overall manufacturing costs. Additionally, this chapter examines the effect of build orientation on the optimized geometry, highlighting how changes in orientation can dramatically affect the volume of support structures and the manufacturability of the final part. We also show that fixing the build orientation for AM in a particular orientation and then performing topology optimization often fails to produce a converged, feasible design solution. The findings underscore the need for a holistic approach to design optimization for metal additive manufacturing, where these AM design factors are simultaneously optimized to achieve practical and efficient designs.

This Special Issue presents the latest advances in the field of fatigue and fracture performances of additively manufactured mechanical components, including components made of traditional materials (metals, sintered steels, etc.) but undergoing complex loading conditions (multiaxial fatigue and mixed mode fracture). This Special Issue is composed of seven papers covering new insights in structural and material engineering. The advent of additive manufacturing (AM) processes applied to the fabrication of structural components creates the need for design methodologies and structural optimization approaches that take into account the specific characteristics of the process. While AM processes give unprecedented geometrical design freedom, which can result in significant reductions of component weight (e.g., through part count reduction), they have implications in the fatigue and fracture strength due to residual stresses and microstructural features. This is due to stress concentration effects and anisotropy that still need research. The papers of this Special Issue report on numerical simulation and experimental work, or a combination of both. The application of damage and fracture mechanics concepts, the appraisal of stress concentration effects, and the consideration of residual stresses and anisotropic behaviour are tackled for a range of structural applications from biomedical engineering to aerospace components.

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

Mechanisms driving high-cycle fatigue life of as-built Inconel 718 processed by laser powder bed fusion

Additive manufacturing of Invar 36 alloy

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.

Support point determination for support structure design in additive manufacturing

Direct-metal additive manufacturing (AM) processes such as Selective Laser Melting (SLM) and Electron Beam Melting (EBM) methods are being used to fabricate complex metallic cellular structures with a laser or electron beam over a metal powder bed. Even though these processes have excellent capabilities to fabricate parts with cellular mesostructures, there exist several constraints in the processes and applications: limited selection of materials, high thermal stress by the high local energy source, poor surface finish, and anisotropic properties of parts caused by combined effects of one-dimensional (1D) energy based patterning mechanism, the deposition layer thickness, powder size, power and travel speed of laser or electron beam. In addition, manufacturing cost is still high with the Direct-metal AM processes. As an alternative for manufacturing metallic 3D cellular structures, which can overcome the disadvantages of direct-metal AM techniques, polymer AM methods may be combined with metal casting. We may call this “Indirect AM based Casting (I AM casting)”. The objective of this study is to explore the potential of I AM Casting associated with development of a novel manufacturing process — Indirect 3D Printing based centrifugal casting which is capable of producing multifunctional metallic cellular structures with internal cooling channels having a 2mm inner diameter and 0.5mm wall thickness. We characterize polymers by making expendable patterns with a polyjet type 3D printer; e.g., modulus, strength, melting and glass transition temperatures and thermal expansion coefficients. A transient flow and heat-transfer analysis of molten metal through 3D cellular network mold will be conducted. Solidification of molten metal through cellular mold during casting will be simulated with temperature dependent properties of molten metal and mold over a range of running temperatures. The volume of fluid (VOF) method will be implemented to simulate the solidification of molten metal together with a user defined function (UDF) of ANSYS/FLUENT. Finally, experimental validation will be conducted.

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) 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.

Sustainability-driven multi-objective evolutionary orienting in additive manufacturing

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.

This work reports the development of robust and efficient algorithms for optimum process planning of Additive Manufacturing (AM) processes needing support structures during fabrication. In particular, it addresses issues like part hollowing, support structure generation and optimum part orientation. Input to the system is a CAD model in STL format which is voxelized and hollowed using the 2D Hollowing strategy. A novel approach to design external as well as internal support structures for the hollowed model is developed considering the wall thickness and material properties. Optimum orientation of the hollowed part model is computed using Genetic Algorithm (GA). The Fitness Function for optimization is the weighted average of process performance parameters like build time, part quality and material utilization. A new performance measure has been proposed to choose the weightages for performance parameters to obtain overall optimum performance. The paper presents, in detail, the design and development of algorithms with results for typical case studies. The proposed methodology will significantly contribute to improving part quality, productivity and material utilization for AM processes.