Physical mechanisms in hybrid additive manufacturing: A process design framework

Recent advances in additive manufacturing (AM) have attracted significant industrial interest. Initially, AM was mainly associated with the fabrication of prototypes, but the AM advances together with the broadening range of available materials, especially for producing metallic parts, have broaden the application areas and now the technology can be used for manufacturing functional parts, too. Especially, the AM technologies enable the creation of complex and topologically optimised geometries with internal cavities that were impossible to produce with traditional manufacturing processes. However, the tight geometrical tolerances along with the strict surface integrity requirements in aerospace, biomedical and automotive industries are not achievable in most cases with standalone AM technologies. Therefore, AM parts need extensive post-processing to ensure that their surface and dimensional requirements together with their respective mechanical properties are met. In this context, it is not surprising that the integration of AM with post-processing technologies into single and multi set-up processing solutions, commonly referred to as hybrid AM, has emerged as a very attractive proposition for industry while attracting a significant R&D interest. This paper reviews the current research and technology advances associated with the hybrid AM solutions. The special focus is on hybrid AM solutions that combine the capabilities of laser-based AM for processing powders with the necessary post-process technologies for producing metal parts with required accuracy, surface integrity and material properties. Commercially available hybrid AM systems that integrate laser-based AM with post-processing technologies are also reviewed together with their key application areas. Finally, the main challenges and open issues in broadening the industrial use of hybrid AM solutions are discussed.

Many inherent issues, such as the detrimental residual stress, columnar grains with anisotropy, and weak mechanical properties, have severely impeded the adoption of metal additive manufacturing (AM) techniques including powder bed fusion and directed energy deposition (DED) processes. In this study, a hybrid AM process that consists of layer-wise laser metal deposition (i.e., a DED process) and in-situ ultrasonic impact peening (UIP) was applied to obtain Inconel 718 superalloy workpieces. Also, for further property enhancement, a post-heat treatment was applied to the deposited material obtained by the hybrid AM process. Scanning electron microscopy and transmission electron microscope were used to investigate the microstructure morphology and reveal the underlying strengthening mechanism. Electron backscatter diffraction was employed to quantitatively study the microstructure resulted from the hybrid AM process and the post-heat treatment. The profile of residual stress along the depth direction was obtained through X-ray diffraction. The results demonstrate that this hybrid AM process is capable of producing high-quality metal parts with significantly refined microstructure, and beneficial compressive residual stress along the depth into surface. Severe plastic strains are introduced by UIP, and the resulted mechanical twinning and dynamic recrystallization play an important role in refining microstructure. The material microstructure is further refined down to 100 µm, and the texture anisotropy is significantly diminished after solution treatment at 980 °C for 1 hour. Under the as-built condition, in-situ ultrasonic peening alters the residual stress component from a tensile state to an overall compressive state with a maximum value of − 190 MPa within the range of measurement depth.

Metal additive manufacturing (AM)-fabricated high-strength aluminum (HS-Al) alloys (2xxx, 6xxx, and 7xxx) tend to produce fatal metallurgical defects such as porosity and cracks. Since Al is the most important lightweight structural material in automotive and aviation industries, successful printing of HS-Al alloys is in high demand. Therefore, this review focuses on the formation mechanisms and research advancements to address these metallurgical defects. Firstly, the process optimization strategies, including AM parameter optimization, hybrid AM processes, and post-processing treatment, and their effectiveness and limitations have been reviewed thoroughly. However, process optimization can address defects such as porosity, surface roughness, and residual stresses but has limited effectiveness on cracking alleviation. Secondly, the research efforts on composition modification to address cracking in AM of HS-Al alloys are critically discussed. Different from process optimization, composition modification alters the solidification dynamics in AM of HS-Al alloys and hence is considered the most promising route for crack-free printing.

Despite the rapid growth in the past decade, the industrial adoption of additive manufacturing has not still been achieved due to certain limitations. A recent trend to alleviate its inherent drawbacks is to integrate additive manufacturing with secondary production techniques. Indeed, hybrid additive manufacturing solutions may help overcome the current barriers to today’s production systems by making use of the combined merits of merging technologies. This paper presents a comprehensive review of the current state-of-the-art in the field, covering the following three key aspects of the subject: (i) advances in the hybridization of additive manufacturing processes, (ii) developments in process planning for integrated technologies, and (iii) insights into the hybrid additive manufacturing industry. The main objective of the paper is to classify the latest knowledge for the researchers, along with highlighting challenges and future research directions in this field.

Fundamental requirements of a machine learning operations platform for industrial metal additive manufacturing

In recent years, Additive Manufacturing (AM), also called 3D printing, has been expanding into several industrial sectors due to the technology providing opportunities in terms of improved functionality, productivity, and competitiveness. While metal AM technologies have almost unlimited potential, and the range of applications has increased in recent years, industries have faced challenges in the adoption of these technologies and coping with a turbulent market. Despite the extensive work that has been completed on the properties of metal AM materials, there is still a need of a robust understanding of processes, challenges, application-specific needs, and considerations associated with these technologies. Therefore, the goal of this study is to present a comprehensive review of the most common metal AM technologies, an exploration of metal AM advancements, and industrial applications for the different AM technologies across various industry sectors. This study also outlines current limitations and challenges, which prevent industries to fully benefit from the metal AM opportunities, including production volume, standards compliance, post processing, product quality, maintenance, and materials range. Overall, this paper provides a survey as the benchmark for future industrial applications and research and development projects, in order to assist industries in selecting a suitable AM technology for their application.

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.

Additive manufacturing is classified as disruptive technology that has the capability to meet new marketplace demands in speed, agility and respond rapidly to fluctuating customer requirements. Applying the design freedom that Additive Manufacturing naturally offers, it is possible to produce complex geometries designed for functionality that are not limited by conventional manufacturing constraints. Speed and efficiency of producing end use parts particularly using metal Additive Manufacturing has significant impact on transforming global supply chain, for offshore segment of oil and gas industry. Metal Additive Manufacturing has been widely adopted in aerospace, defense and medical device industries and is an emerging technology in oil and gas where it is gradually gaining acceptance. However, industrialization of the technology requires process repeatability with efficient workflows and reliable part production. Every step in the process chain has an effect on the integrity and quality of the end product, therefore implementing process control across the Additive Manufacturing value chain is essential to enable its use as mainstream manufacturing technology. This article reviews available and evolving methods to achieve a controlled Additive Manufacturing process for metallic materials.

Purpose The development of additive manufacturing (AM) techniques has significantly expanded the design space for engineering structures and facilitated the practical application of novel concepts, such as meta-materials with diverse microstructures. However, in load-bearing applications—particularly in aerospace and aeroengine fields—additively manufactured (AMed) metallic materials and structures still face limitations due to the presence of inherent defects. For meta-materials, the geometric accuracy of microstructural cells is also difficult to ensure using current metal AM technologies. These defects and geometric inaccuracies can markedly affect the mechanical properties of mechanical meta-materials. Consequently, a substantial body of research has focused on investigating the mechanical behavior and performance of AMed mechanical meta-materials. This paper presents a comprehensive review of recent advancements in metal AM technologies, with a particular focus on defect characterization methods and the evaluation of strength and fatigue properties in AMed mechanical meta-materials. Design/methodology/approach This paper provides a state-of-the-art review on the AM techniques for mechanical meta-materials, defects and defect characterization methods in AMed structures, and evaluation methods of strength and fatigue properties of mechanical meta-materials. Findings Metal AM techniques for mechanical meta-materials, like selective laser melting, wire-arc AM, etc, and recently developed technologies like, online inspection during the AM process, are reviewed. The defects in AMed meta-materials, along with the corresponding characterization methods, are systematically summarized. Additionally, this paper presents a comprehensive overview of evaluation approaches for the strength and fatigue properties of mechanical meta-materials, encompassing experimental testing, theoretical modeling, numerical simulation, and machine learning techniques. Future perspectives on manufacturing and the mechanical property study of mechanical meta-materials are also given. Originality/value A systematic summary of metal AM techniques, as well as defect detection and characterization methods in AMed mechanical meta-materials, is provided. Furthermore, the paper presents a comprehensive review of the mechanical properties of mechanical meta-materials, with a particular focus on strength and fatigue performance.

The manufacturing industry is undergoing a profound transformation driven by increasing demands for efficiency, customization, and sustainability. Although Additive Manufacturing (AM) offers significant advantages, its industrial adoption remains constrained by limitations in precision, productivity, and repeatability. Hybrid Additive Manufacturing (HAM), which integrates additive and conventional manufacturing processes, has emerged as a promising pathway to overcome these limitations. This study goes beyond descriptive literature mapping by combining bibliometric science mapping with Technology Life Cycle (TLC) modelling to analyse the evolution, technological maturity, and industrial positioning of HAM. Using a Scopus dataset and the Gompertz growth model, the study interprets publication and citation dynamics. The results indicate that HAM is currently in an early growth phase, with differentiated maturity trajectories across process families and a projected inflection point around 2030. By linking bibliometric clusters to technological maturity, the study reveals mismatches between scientific activity and industrial deployment, as well as the role of international collaboration in shaping impact and specialization. Based on this integrated analysis, the paper derives actionable research priorities and industrial implications, addressing process reliability, hybrid process planning, material–process co-optimization, and certification challenges. Rather than providing a purely descriptive overview, this study offers an analytical framework that supports strategic decision-making for researchers, industry stakeholders, and policymakers, contributing to the advancement of hybrid manufacturing technologies.

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.

Metal additive manufacturing: Principles and applications

Additive manufacturing (AM) technologies enable near-net-shape designs and demand-oriented material usage, which significantly minimizes waste. This points to a substantial opportunity for further optimization in material savings and process design. The current study delves into the advancement of sustainable manufacturing practices in the automotive industry, emphasizing the crucial role of lightweight construction concepts and AM technologies in enhancing resource efficiency and reducing greenhouse gas emissions. By exploring the integration of novel AM techniques such as selective laser melting (SLM) and laser metal deposition (LMD), the study aims to overcome existing limitations like slow build-up rates and limited component resolution. The study’s core objective revolves around the development and validation of a continuous process chain that synergizes different AM routes. In the current study, the continuous process chain for DMG MORI Lasertec 65 3D’s LMD system and the DMG MORI Lasertec 30 3D’s was demonstrated using 316L and 1.2709 steel materials. This integrated approach is designed to significantly curtail process times and minimize component costs, thus suggesting an industry-oriented process chain for future manufacturing paradigms. Additionally, the research investigates the production and material behavior of components under varying manufacturing processes, material combinations, and boundary layer materials. The culmination of this study is the validation of the proposed process route through a technology demonstrator, assessing its scalability and setting a benchmark for resource-efficient manufacturing in the automotive sector.

Nondestructive evaluation of micro-oxide inclusions in additively manufactured metal parts using nonlinear ultrasonic technique

Cutting fluids in metal AM: A review of sustainability and efficiency