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This 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.

A 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.

The 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.

This 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.

This 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.

Injection molding is a very mature technology, but the growth of layer‐build, additive, manufacturing technologies (rapid prototypying) has the potential of expanding injection molding into areas not commercially feasible with traditional molds and molding techniques. This integration of injection molding with rapid prototyping has undergone many demonstrations of potential. What is missing is the fundamental understanding of how the modifications to the mold material and mold manufacturing process impact both the mold design and the injection molding process. This work expanded on an approach to utilize current numerical simulation programs and created a tool for optimizing the creation and use of non‐metal molds for injection molding. Verification and validation work is presented. The model was exercised by studying the effect of varying the thermal conductivity on final‐part distortions. This work clearly showed that one could not obtain reasonable results by simply changing a few input parameters in the current simulations. Although the approach did produce more realistic results, more work will be required for a tool capable of accurate, quantitative predictions.

This study aims to develop a novel thermal modeling strategy to simulate electron beam powder bed fusion at part scale with machine-varying process parameters strategy. Single-bead and part-scale experiments and modeling were studied. Scanning strategies were described by the process controlling functions that enabled modeling.

The finite element analysis thermal model was used along with the powder bed fusion with electron beam experiments. The proposed strategy involves dividing a part into smaller sections and creating meso-scale models for each subsection. These meso-scale models take into consideration the variable process parameters, including power and velocity of the moving heat source, during part building. Subsequently, these models are integrated to perform partscale simulations, enabling more realistic predictions of thermal accumulation and resulting distortions. The model was built and validated with single-bead experiments and bulky parts with different features.

Single-bead experiments demonstrated an average error rate of 6%–24% for melt pool dimension prediction using the proposed meso-scale models with different scanning control functions. Part-scale simulations for three different geometries (cantilever beams with supports, bulk artifact and topology-optimized transfer arm) showed good agreement between modeled temperature changes and experimental deformation values.

This study presents a novel approach for electron beam powder bed fusion modeling that leverages meso-scale models to capture the influence of variable process parameters on part quality. This strategy offers improved accuracy for predicting part geometry and identifying potential defects, leading to a more efficient additive manufacturing process.

The treatment of Reynolds equation when the film thickness is unknown and the center of pressure is known, together with the energy and the bending equation, allows a realistic simulation of the performance of large thrust bearing. In a spring‐supported thrust‐pad bearing the distortion caused by the generated pressure thermal gradient yields a surface profile of opposite shapes. The thermoelastic analysis performed here makes it possible to determine the resultant film shape of the thrust pad.

This paper aims to present a survey concerning the accuracy of thermoplastic polymeric parts fabricated by additive manufacturing (AM). Based on the scientific literature, the aim is to provide an updated map of trends and gaps in this relevant research field. Several technologies and investigation methods are examined, thus giving an overview and analysis of the growing body of research.

Permutations of keywords, which concern materials, technologies and the accuracy of thermoplastic polymeric parts fabricated by AM, are used for a systematic search in peer-review databases. The selected articles are screened and ranked to identify those that are more relevant. A bibliometric analysis is performed based on investigated materials and applied technologies of published papers. Finally, each paper is categorised and discussed by considering the implemented research methods.

The interest in the accuracy of additively manufactured thermoplastics is increasing. The principal sources of inaccuracies are those shrinkages occurring during part solidification. The analysis of the research methods shows a predominance of empirical approaches. Due to the experimental context, those achievements have consequently limited applicability. Analytical and numerical models, which generally require huge computational costs when applied to complex products, are also numerous and are investigated in detail. Several articles deal with artificial intelligence tools and are gaining more and more attention.

The cross-technology survey on the accuracy issue highlights the common critical aspects of thermoplastics transformed by AM. An updated map of the recent research literature is achieved. The analysis shows the advantages and limitations of different research methods in this field, providing an overview of research trends and gaps.

The purpose of this study is to develop a novel comprehensive three-dimensional computational model to predict the transient thermal behavior and residual stresses resulting from the layer-by-layer deposition in the direct metal laser sintering process.

In the proposed model, time integration is performed with an implicit scheme. The equations for heat transfer are discretized by a finite volume method with thermophysical properties of the metal powder and an updated convection coefficient at each time step. The model includes convective and radiative boundary conditions for the exposed surfaces of the part and constant temperatures for the bottom surface on the build plate. The laser source is modeled as a moving radiative heat flux along the scanning pattern, while the thermal gradients are used to calculate directional and von Mises residual thermal stresses by using a quasi-steady state assumption.

In this study, four different scanning patterns are analyzed, and the transient temperature and residual thermal stress fields are evaluated from these patterns. It is found that the highest stresses occur where the laser last leaves off on its scanning pattern for each layer.

The proposed model is designed to capture the layer-by-layer deposition for a three-dimensional geometry while considering the effect of the instantaneous melting of the powder, melt pool, dynamic calculation of thermophysical properties, ease of parametrization of various process parameters and the vectorization of the code for computational efficiency. This versatile model can be used for process parameter optimization of other laser powder bed fusion additive manufacturing techniques. Furthermore, the proposed approach can be used for analyzing different scanning patterns.

The usage of additive manufacturing (AM) technology in industries has reached up to 50 per cent as prototype or end-product. However, for AM products to be directly used as final products, AM product should be produced through advanced quality control process, which has a capability to be able to prove and reach their desire repeatability, reproducibility, reliability and preciseness. Therefore, there is a need to review quality-related research in terms of AM technology and guide AM industry in the future direction of AM development.

This paper overviews research progress regarding the QC in AM technology. The focus of the study is on manufacturing quality issues and needs that are to be developed and optimized, and further suggests ideas and directions toward the quality improvement for future AM technology. This paper is organized as follows. Section 2 starts by conducting a comprehensive review of the literature studies on progress of quality control, issues and challenges regarding quality improvement in seven different AM techniques. Next, Section 3 provides classification of the research findings, and lastly, Section 4 discusses the challenges and future trends.

This paper presents a review on quality control in seven different techniques in AM technology and provides detailed discussions in each quality process stage. Most of the AM techniques have a trend using in-situ sensors and cameras to acquire process data for real-time monitoring and quality analysis. Procedures such as extrusion-based processes (EBP) have further advanced in data analytics and predictive algorithms-based research regarding mechanical properties and optimal printing parameters. Moreover, compared to others, the material jetting progresses technique has advanced in a system integrated with closed-feedback loop, machine vision and image processing to minimize quality issues during printing process.

This paper is limited to reviewing of only seven techniques of AM technology, which includes photopolymer vat processes, material jetting processes, binder jetting processes, extrusion-based processes, powder bed fusion processes, directed energy deposition processes and sheet lamination processes. This paper would impact on the improvement of quality control in AM industries such as industrial, automotive, medical, aerospace and military production.

Additive manufacturing technology, in terms of quality control has yet to be reviewed.

The lightweight design of aircraft seats can significantly improve fuel efficiency and reduce greenhouse gas emissions. Metal additive manufacturing (MAM) can produce lightweight topology-optimized designs with improved performance, but limited build volume restricts the printing of large components. The purpose of this paper is to design a lightweight aircraft seat leg structure using topology optimization (TO) and MAM with build volume restrictions, while satisfying structural airworthiness certification requirements.

TO was used to determine a lightweight conceptual design for the seat leg structure. The conceptual design was decomposed to meet the machine build volume, a detailed CAD assembly was designed and print orientation was selected for each component. Static and dynamic verification was performed, the design was updated to meet the structural requirements and a prototype was manufactured.

The final topology-optimized seat leg structure was decomposed into three parts, yielding a 57% reduction in the number of parts compared to a reference design. In addition, the design achieved an 8.5% mass reduction while satisfying structural requirements for airworthiness certification.

To the best of the authors’ knowledge, this study is the first paper to design an aircraft seat leg structure manufactured with MAM using a rigorous TO approach. The resultant design reduces mass and part count compared to a reference design and is verified with respect to real-world aircraft certification requirements.

The purpose of this paper is to report experimental investigations performed to analyze the effect of process parameters on the shape accuracy of selective laser sintered (SLS) parts.

The effect of process parameters, namely build orientation, laser power, scan speed, cylinder diameter and build chamber temperature has been studied on shape accuracy by using geometric tolerances such as cylindricity and flatness. Central composite design (CCD) is used to plan the experiments and a second order regression model has been developed to predict flatness and cylindricity. The significance of process variables on flatness and cylindricity has been evaluated using analysis of variance technique.

It is observed that interaction effects are more dominant than individual effects. In case of cylindricity, it is found that the interaction between the scan speed and orientation is the dominant factor next to the orientation and quadratic effect of the geometry. In case of flatness, the interaction between build chamber temperature and scan speed is the dominant factor.

The empirical models presented in this paper work within the range of values used for the experiments and most of these models need to be redeveloped for use with other materials.

The empirical models developed in this work would be useful in deciding the process parameters for parts with improved geometrical tolerances. The optimum parameters identified from the empirical model are found to yield accurate parts with minimum shape error.

The paper establishes the interactions between this build orientation, geometry and process parameters on the shape accuracy of SLS process.

This paper aims to address the numerical simulation of additive manufacturing (AM) processes. The numerical results are compared with the experimental campaign carried out at State Key Laboratory of Solidification Processing laboratories, where a laser solid forming machine, also referred to as laser engineered net shaping, is used to fabricate metal parts directly from computer-aided design models. Ti-6Al-4V metal powder is injected into the molten pool created by a focused, high-energy laser beam and a layer of added material is sinterized according to the laser scanning pattern specified by the user.

The numerical model adopts an apropos finite element (FE) activation technology, which reproduces the same scanning pattern set for the numerical control system of the AM machine. This consists of a complex sequence of polylines, used to define the contour of the component, and hatches patterns to fill the inner section. The full sequence is given through the common layer interface format, a standard format for different manufacturing processes such as rapid prototyping, shape metal deposition or machining processes, among others. The result is a layer-by-layer metal deposition which can be used to build-up complex structures for components such as turbine blades, aircraft stiffeners, cooling systems or medical implants, among others.

Ad hoc FE framework for the numerical simulation of the AM process by metal deposition is introduced. Description of the calibration procedure adopted is presented.

The objectives of this paper are twofold: firstly, this work is intended to calibrate the software for the numerical simulation of the AM process, to achieve high accuracy. Secondly, the sensitivity of the numerical model to the process parameters and modeling data is analyzed.