Characterisation methods for powder bed fusion processed surface topography

Metal Additive Manufacturing (AM) is increasingly being used to make functional components. One of the barriers for AM components to become mainstream is the difficulty to certify them. AM components can have widely different properties based on process parameters. Improving an AM processes requires an understanding of process-structure-property correlations, which can be gathered in-situ and post-process through nondestructive and destructive methods. In this study, two metal AM processes were studied, the first is Ultrasonic Additive Manufacturing (UAM) and the second is Laser Powder Bed Fusion (L-PBF). The typical problems with UAM components are inter-layer and inter-track defects. To improve the UAM process, an in-situ quality evaluation technique was desired. Several NDE techniques were tested in a lab environment before ultrasonic NDE was chosen as a practical, robust, and cost-effective NDE tool. An in-situ monitoring setup was designed and built on an UAM system. NDE results showed interesting features that were simulated through analytic and finite element wave-propagation models. AM layers with defects were characterized as an intact layer and a finite interfacial stiffness spring. The spring stiffness coefficient is a quality parameter that was used to characterize AM layers through a model-based inversion method. In-situ and post-process NDE provided an understanding of defect generation and propagation in UAM. A novel solid-state repair mechanism based on Friction Stir Processing (FSP) was proposed and demonstrated. The quality of L-PBF components depends on several factors including laser power, scan speed, hatch spacing, layer thickness, particle shape/size distribution and other build conditions. Developing process parameters for a new material is an expensive and complex optimization problem. Post-process ultrasonic NDE tests revealed that the model-based in-situ quality monitoring developed for UAM is also applicable to L-PBF Additive Manufacturing. A similar NDE set-up was designed and installed on an open-architecture L-PBF system. A layer-by-layer bond quality evaluation demonstrates the ability to detect good-quality bonds hidden behind poor-quality regions for Inconel 625 alloy. A cost-effective, process parameter development methodology has been proposed and demonstrated.

Influence of defects and as-built surface roughness on fatigue properties of additively manufactured Alloy 718

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.

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.

Beam-based additive manufacturing (AM) is an innovative technique in which parts are built layerwise, starting from the material in powder form. As a developing manufacturing technique, achievement of excellent mechanical properties in the final part is of paramount importance for the mainstream adoption of this technique in industrial manufacturing lines. At the same time, AM offers an unprecedented opportunity to precisely control the manufacturing conditions locally within the part during build, enabling local influence on the formation of the texture and microstructure. In order to achieve the control of microstructure by tailoring the AM machine parameters, a full understanding and modeling of the heat transfer and microstructure evolution processes is needed. Here, we show the implementation of the non-equilibrium equations for phase formation and dissolution in an AM modeling framework. The model is developed for the Ti6Al4V alloy and allows us to show microstructure evolution as given by the AM process. The developed capability is applied to the cases of electron beam melting and selective laser melting AM techniques to explain the significantly different microstructures observed in the two processes.

Indirect additive manufacturing based casting of a periodic 3D cellular metal – Flow simulation of molten aluminum alloy

Complex geometry, variable macrostructure, anisotropy, distributed defects, surface roughness, and residual stresses of additively manufactured (AM) components challenge nondestructive evaluation processes developed and validated for conventional manufacturing. Electromagnetic and eddy current (EC) technologies were identified as promising for in-process, real-time monitoring, and post-process examination of AM components. Powder and solid specimens were prepared for electromagnetic property measurements and technique development and optimization. The post-process specimens were fabricated with roughness representative of surface conditions during fabrication inside the AM machine. Artificial and natural discontinuities were fabricated with the electrical discharge machining process and by varying the laser fusion parameters. Extensive computed modeling was conducted to develop an optimized array EC (AEC) sensor and technique for AM real-time monitoring. The AEC sensor could withstand temperatures up to 100ºC. Computational modeling was conducted to investigate the likelihood of metal powder disturbance by the EC sensor electromagnetic field. A real-time data acquisition system was assembled and integrated with an open-architecture laser powder bed fusion (L-PBF) test bed. The EC system performance for real-time monitoring of the L-PBF process was demonstrated through layer-by-layer testing of Inconel 625 coupons, with AM built discontinuities and lack of fusion. The L-PBF process was representative of a typical AM process used for super alloys and steels with preheat of substrate plate and AM test specimens to 100ºC. Existing AEC equipment and techniques were used for post-process examination of AM solid specimens at room temperatures. The AEC technology demonstrated excellent sensitivity to seeded and natural surface and near-surface subsurface discontinuities and surface topography during real-time monitoring and post-processing. Electromagnetic and EC techniques were demonstrated to examine powder before fabrication. The application of modeling tools reduced developmental time and improved efficiency. Further research and development was recommended to improve data acquisition process and transition AEC monitoring technology to other AM processes.

Fatigue life of additively manufactured Ti–6Al–4V in the very high cycle fatigue regime

This article is a detailed account of additive manufacturing (AM) processes for copper and copper alloys such as copper-chromium alloys, GRCop, oxide-dispersion-strengthened copper, copper-nickel alloys, copper-tin alloys, copper-zinc alloys, and copper-base shape memory alloys. The AM processes include binder jetting, ultrasonic additive manufacturing, directed-energy deposition, laser powder-bed fusion, and electron beam powder-bed fusion. The article presents a review of the literature and state of the art for copper alloy AM and features data on AM processes and industrial practices, copper alloys used, selected applications, material properties, and where applicable, compares these data and properties to traditionally processed materials. The data presented and the surrounding discussion focus on bulk metallurgical processing of copper components. The discussion covers the composition and performance criteria for copper alloys that have been reported for AM and discusses key differences in process-structure-property relationships compared to conventionally processed material. The article also provides information on feedstock considerations for copper powder handling.

Although the additive manufacturing (AM) market continues to grow, industries face barriers to AM adoption due to a shortage of skilled designers in the workforce that can apply AM effectively to meet this demand. This shortage is attributed to the high cost and infrastructural requirements of introducing high- barrier-to-entry AM processes such as powder bed fusion (PBF) into in-person learning environments. To meet the demands for a skilled AM workforce, it is important to explore other mediums of AM education, such as computer-aided instruction (CAI) and virtual reality (VR), which can increase access to hands-on learning experiences for inaccessible AM processes. However, limited work compares virtual and physical AM instruction or explores how the differences in immersion and presence between mediums can affect the knowledge gained and the mental effort exerted when learning about different AM processes. To address this gap in the literature, this research evaluates the use of CAI, VR, and in-person instruction in AM process education when learning about material extrusion (ME) and PBF. Our findings show that the differences in immersion and presence between CAI, VR, and in-person instruction do not have a statistically significant effect when learning about ME, but do have a significant effect when learning about PBF. Specifically, we found that VR generally yields equivalent effects in knowledge gain and cognitive load to in-person PBF education while offering advantages in both metrics over CAI learning. The findings from this work thus have significant implications for using VR as an alternative to in-person training to improve designer development in process-centric AM education of typically high-barrier-to-entry AM processes.

Additive manufacturing (AM) or 3D printing is a promising industrial technology that enables rapid prototyping of complex configurations. Powder Bed Fusion (PBF) is one of the most popular AM techniques for metallic materials. Until today, only a few metals and alloys are available for AM, e.g., titanium alloys, the most common of which is Ti-6Al-4V. After optimization of PBF parameters, with or without post processing such as heat treatment or hot isostatic pressing, the printed titanium alloy can easily reach tensile strengths of over 1100 MPa due to the quick cooling of the AM process. However, attributed to the unique features of metallurgical defects and microstructure introduced by this AM process, their fatigue strength has been low, often less than 30% of the tensile strength, especially in very-high-cycle regimes, i.e., failure life beyond 107 cycles. Here, based on our group’s research on the very-high-cycle fatigue (VHCF) of additively manufactured (AMed) Ti-6Al-4V alloys, we have refined the basic quantities of porosity, metallurgical defects, and the AMed microstructure, summarized the main factors limiting their VHCF strengths, and suggested possible ways to improve VHCF performance.

Additive manufacturing (AM) is an emerging process that has been extremely improved in terms of technology and application in recent years. In this technology review, new industrial improvements in laser powder bed fusion (LPBF) of metals are discussed. LPBF has the lowest build rate among all AM processes that produce metals such as electron beam powder bed fusion, direct energy deposition, binder jetting and sheet lamination. The findings of the current research show that the most innovations and future directions of LPBF printers are toward increasing the speed of the process by using interchangeable feedstock chamber, closed-loop control powder handling, automated powder sieving, multi-layer concurrent printing, 2-axis coating and multi powder hoppers. To increase the speed of the process, the new improvements for transferring time and using fast lasers are presented. Another innovation in the building of LPBF printers is enhancing part quality by improving lasers with the shorter beam diameter, multi-lasers, uniform inert gas flow, accurate positioning systems, using high vacuum systems and using sensors and automation.

Chapter 14 - Laser aided metal additive manufacturing and postprocessing: a comprehensive review

Current understanding and challenges in high temperature additive manufacturing of engineering thermoplastic polymers