Chapter 1 - Metal additive manufacturing

Metal additive manufacturing: Principles and applications

Metal Powder Production for Additive Manufacturing

Additive manufacturing (AM) of hot-work tool steels such as H13 offers unique opportunities for producing complex, conformally cooled tools with reduced production time and material waste. In this study, five metal AM technologies—Fused Deposition Modeling and Sintering (FDMS, Desktop Metal Studio System and Zetamix), Binder Jetting (BJ), Laser Powder Bed Fusion (LPBF), and Directed Energy Deposition (DED)—were compared in terms of microstructure, porosity, and post-processing heat treatment response. The as-printed microstructures revealed distinct differences among the technologies: FDMS and BJ exhibited high porosity (6–9%), whereas LPBF and DED achieved near-full densification (<0.1%). Samples with sufficiently low porosity (BJ, LPBF, DED) were subjected to tempering and quenching treatments to evaluate hardness evolution and microstructural transformations. The satisfactory post-treatment hardness was observed in both tempered and quenched and tempered BJ samples, associated with secondary carbide precipitation, while LPBF and DED samples retained stable martensitic structures with hardness around 600 HV0.5. Microstructural analyses confirmed the dependence of phase morphology and carbide distribution on the thermal history intrinsic to each AM process. The study demonstrates that while FDMS and BJ are more accessible and cost-effective for low-density prototypes, LPBF and DED offer superior density and mechanical integrity suitable for functional tooling applications.

Laser-based directed energy deposition (DED-LB) of advanced materials

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.

PurposeAdditive manufacturing (AM) is a rapidly evolving manufacturing process, which refers to a set of technologies that add materials layer-by-layer to create functional components. AM technologies have received an enormous attention from both academia and industry, and they are being successfully used in various applications, such as rapid prototyping, tooling, direct manufacturing and repair, among others. AM does not necessarily imply building parts, as it also refers to innovation in materials, system and part designs, novel combination of properties and interplay between systems and materials. The most exciting features of AM are related to the development of radically new systems and materials that can be used in advanced products with the aim of reducing costs, manufacturing difficulties, weight, waste and energy consumption. It is essential to develop an advanced production system that assists the user through the process, from the computer-aided design model to functional components. The challenges faced in the research and development and operational phase of producing those parts include requiring the capacity to simulate and observe the building process and, more importantly, being able to introduce the production changes in a real-time fashion. This paper aims to review the role of robotics in various AM technologies to underline its importance, followed by an introduction of a novel and intelligent system for directed energy deposition (DED) technology.Design/methodology/approachAM presents intrinsic advantages when compared to the conventional processes. Nevertheless, its industrial integration remains as a challenge due to equipment and process complexities. DED technologies are among the most sophisticated concepts that have the potential of transforming the current material processing practices.FindingsThe objective of this paper is identifying the fundamental features of an intelligent DED platform, capable of handling the science and operational aspects of the advanced AM applications. Consequently, we introduce and discuss a novel robotic AM system, designed for processing metals and alloys such as aluminium alloys, high-strength steels, stainless steels, titanium alloys, magnesium alloys, nickel-based superalloys and other metallic alloys for various applications. A few demonstrators are presented and briefly discussed, to present the usefulness of the introduced system and underlying concept. The main design objective of the presented intelligent robotic AM system is to implement a design-and-produce strategy. This means that the system should allow the user to focus on the knowledge-based tasks, e.g. the tasks of designing the part, material selection, simulating the deposition process and anticipating the metallurgical properties of the final part, as the rest would be handled automatically.Research limitations/implicationsThis paper reviews a few AM technologies, where robotics is a central part of the process, such as vat photopolymerization, material jetting, binder jetting, material extrusion, powder bed fusion, DED and sheet lamination. This paper aims to influence the development of robot-based AM systems for industrial applications such as part production, automotive, medical, aerospace and defence sectors.Originality/valueThe presented intelligent system is an original development that is designed and built by the co-authors J. Norberto Pires, Amin S. Azar and Trayana Tankova.

The goal of this work is to predict the effect of part geometry and process parameters on the instantaneous spatiotemporal distribution of temperature, also called the thermal field or temperature history, in metal parts as they are being built layer-by-layer using additive manufacturing (AM) processes. In pursuit of this goal, the objective of this work is to develop and verify a graph theory-based approach for predicting the temperature distribution in metal AM parts. This objective is consequential to overcome the current poor process consistency and part quality in AM. One of the main reasons for poor part quality in metal AM processes is ascribed to the nature of temperature distribution in the part. For instance, steep thermal gradients created in the part during printing leads to defects, such as warping and thermal stress-induced cracking. Existing nonproprietary approaches to predict the temperature distribution in AM parts predominantly use mesh-based finite element analyses that are computationally tortuous—the simulation of a few layers typically requires several hours, if not days. Hence, to alleviate these challenges in metal AM processes, there is a need for efficient computational models to predict the temperature distribution, and thereby guide part design and selection of process parameters instead of expensive empirical testing. Compared with finite element analyses techniques, the proposed mesh-free graph theory-based approach facilitates prediction of the temperature distribution within a few minutes on a desktop computer. To explore these assertions, we conducted the following two studies: (1) comparing the heat diffusion trends predicted using the graph theory approach with finite element analysis, and analytical heat transfer calculations based on Green’s functions for an elementary cuboid geometry which is subjected to an impulse heat input in a certain part of its volume and (2) simulating the laser powder bed fusion metal AM of three-part geometries with (a) Goldak’s moving heat source finite element method, (b) the proposed graph theory approach, and (c) further comparing the thermal trends predicted from the last two approaches with a commercial solution. From the first study, we report that the thermal trends approximated by the graph theory approach are found to be accurate within 5% of the Green’s functions-based analytical solution (in terms of the symmetric mean absolute percentage error). Results from the second study show that the thermal trends predicted for the AM parts using graph theory approach agree with finite element analyses, and the computational time for predicting the temperature distribution was significantly reduced with graph theory. For instance, for one of the AM part geometries studied, the temperature trends were predicted in less than 18 min within 10% error using the graph theory approach compared with over 180 min with finite element analyses. Although this paper is restricted to theoretical development and verification of the graph theory approach, our forthcoming research will focus on experimental validation through in-process thermal measurements.

Inconel 718 is a nickel-based superalloy known for its excellent combination of high-temperature strength, corrosion resistance, and weldability. Additive Manufacturing (AM) has revolutionized traditional manufacturing processes by enabling the creation of complex and customized components. In this work, three prominent AM techniques: Laser-Based Powder Bed Fusion (PBF), Wire Direct Energy Deposition (DED), and Binder Jet (BJ) processes were explored. A thorough metallographic analysis and comparison of samples was conducted after short-term creep testing originating from each of the three aforementioned techniques in addition to wrought material. Detailed electron microscopy unveiled equiaxed grains in both BJ and wrought samples while PBF samples displayed elongated finer grain structures in the build direction, characteristic of PBF. The DED samples revealed a more bimodal grain distribution with a combination of smaller equiaxed grains accompanied by larger more elongated grains. When assessing the three processes, the average grain size was found to be larger in the BJ samples, while the PBF samples exhibited the most significant variation in grain and sub-grain size. Number density, size, and shape of porosity varied between all three techniques. Post-creep test observations in PBF samples revealed the occurrence of wedge cracking at the failure point, accompanied by a preference for grain boundary creep void formation while BJ samples exhibited grain boundary creep void coalescence and cracking at the failure location. In the DED samples, void formation was minimal however, it seemed to be more prevalent in areas with precipitates. In contrast, the wrought sample showed void formation at the failure site with a preference for areas with primary carbide formation. Despite BJ samples demonstrating similar or even superior rupture life compared to other AM techniques, a noteworthy reduction in rupture ductility was observed. While a coarse, uniform grain size is generally linked to enhanced creep resistance and rupture life, the combination of pre-existing voids along grain boundaries and the formation of new voids is hypothesized to accelerate rapid fracture, resulting in diminished ductility. This research shows careful consideration is needed when selecting an AM technology for high- temperature applications as creep behavior is sensitive to the large microstructural variations AM can introduce.

Nanoporous materials are categorized as microporous (pore sizes 0.2-2nm), mesoporous (pore sizes 2-50nm), and macroporous (pore sizes 50-1000nm). Mesoporous silica (MS) has gained a significant interest due to its notable characteristics, including organized pore networks, specific surface areas, and the ability to be integrated in a variety of morphologies. Recently, MS has been widely accepted by range of manufacturer and as drug carrier. Moreover, silica nanoparticles containing mesopores, also known as mesoporous silica nanoparticles (MSNs), have attracted widespread attention in additive manufacturing (AM). AM commonly known as three-dimensional printing is the formalized rapid prototyping (RP) technology. AM techniques, in comparison to conventional methods, aid in reducing the necessity for tooling and allow versatility in product and design customization. There are generally several types of AM processes reported including VAT polymerization (VP), powder bed fusion (PBF), sheet lamination (SL), material extrusion (ME), binder jetting (BJ), direct energy deposition (DED), and material jetting (MJ). Furthermore, AM techniques are utilized in fabrication of various classified fields such as architectural modeling, fuel cell manufacturing, lightweight machines, medical, and fabrication of drug delivery systems. The review concisely elaborates on applications of mesoporous silica as versatile material in fabrication of various AM-based pharmaceutical products with an elaboration on various AM techniques to reduce the knowledge gap.

Additive manufacturing (AM) has revolutionized the production of complex geometrical parts with metals; however, the usual layer-by-layer deposition results in poor surface quality and unpredictable surface integrity. Abrasive machining and finishing techniques play vital roles in counteracting these challenges and qualifying AM parts for practical applications. This review aims to present recent research developments concerning the machining of additively manufactured metal parts via both conventional and nonconventional abrasive machining methods. Conventional methods such as grinding, milling, polishing, honing, and sandblasting have been widely investigated for their ability to enhance the surface finish, dimensional accuracy, and mechanical properties of AM metal components. However, the characteristic features of various AM processes, such as porosity, microstructural features, and residual stresses, can significantly influence the machinability of the produced parts. Nonconventional methods such as abrasive flow machining, electrochemical machining, magnetic abrasive finishing, and vibratory bowl finishing, on the other hand, have shown potential in addressing the difficulties associated with internal machining geometries and hard-to-machine material combinations that are typical for many AM parts. This review also highlights some challenges and future trends in the machining of AM metal parts and emphasizes that further research is required in the direction of combinations of various postprocessing techniques, machinability regarding new alloy compositions, and the integration of AI for process optimization. As the demand for high-precision AM parts grows across various industries, the advancement of abrasive machining and finishing techniques is crucial for driving the wider adoption of AM technologies.

The flexibility offered by additive manufacturing (AM) technologies to fabricate complex geometries poses several challenges to non-destructive evaluation (NDE) and quality control (QC) techniques. Existing NDE and QC techniques are not optimized for AM processes, materials, or parts. Such lack of reliable means to verify and qualify AM parts is a significant barrier to further industrial adoption of AM technologies. Electromechanical impedance measurements have been recently introduced as an alternative solution to detect anomalies in AM parts. With this approach, piezoelectric wafers bonded to the part under test are utilized as collocated sensors and actuators. Due to the coupled electromechanical characteristics of piezoelectric materials, the measured electrical impedance of the piezoelectric wafer depends on the mechanical impedance of the part under test, allowing build defects to be detected. This paper investigates the effectiveness of impedance-based NDE approach to detect internal porosity in AM parts. This type of build defects is uniquely challenging as voids are normally embedded within the structure and filled with unhardened model or supporting material. The impact of internal voids on the electromechanical impedance of AM parts is studied at several frequency ranges.

Chapter 4 - 3D printing composite materials: A comprehensive review

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.

Abstract. Recently, there has been an increasing interest in hybrid additive manufacturing (HAM) technologies to overcome the limits of conventional and additive manufacturing (AM) technologies. In the case of metals, HAM can be used to combine AM with forming operations. This concept can be applied in both the production of bulk and sheet metal parts. When sheet metal parts are taken into consideration, usually AM technology such as laser powder bed fusion (L-PBF) and direct energy deposition (DED) can be combined with traditional forming operations. L-PBF is preferred when small details have to be applied to the metal sheet before undergoing the forming process. Thus, mass customization can be achieved by using the flexibility of the AM process, its ability to print complex geometries, and the speed of the sheet metal forming process. In this study, a numerical model was developed in order to analyze the influence of the L-PBF process on the metal sheet. The results show how the metal sheet is strongly influenced by the thermal input due to the deposition of the AM part. Moreover, the presence of residual stress can be observed within the metal sheet, which can result in distortion and create problems in the following forming step. The numerical model highlights also the more critical area, in which high-stress concentration is observed.

Sinter-based metal additive manufacturing (AM) processes that decouple the geometric shaping and consolidation of AM have several advantages over melt-based AM technologies (one-step consolidation and shaping). The sinter-based AM technologies, led by binder jetting, has the potential to significantly increase the productivity and attain more isotropic microstructures in the final product. Sinter-based AM includes the ability to cover a wide spectrum of productivity, including prototyping, low volume serial production, and high-volume mass production. Recently, several non-traditional sinter-based metal AM processes (relatively less common) have emerged. This paper will review some of these emerging and lesser-known sinter-based metal AM technologies along with a few processes based on modifications of binder jet and material extrusion techniques that have gained traction.