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Although many researchers have widely studied additive manufacturing (AM) as one of the most important industrial revolutions, few have presented a bibliometric analysis of the published studies in this area. This paper aims to evaluate AM research trends based on 4607 publications most cited from year 2010 to 2020.

The research methodology is bibliometric indicators and network analysis, including analysis based on keywords, citation analysis, productive journal, related published papers and authors indicators. Two free available software were employed VOSviewer and Bibexcel.

Keywords analysis results indicate that among the AM processes, Selective Laser Melting and Fused Deposition Modeling techniques, are the two processes ranked on top of the techniques employed and studied with 35.76% and 20.09% respectively. The citation analysis by VOSviewer software, reveals that the medical applications field and the fabrication of metal parts are the areas that interest researchers greatly. Different new research niches, as pharmaceutical industry, digital construction and food fabrication are growing topics in AM scientific works. This study reveals that journals “Materials & design”, “Advanced materials”, “Acs applied materials & interfaces”, “Additive manufacturing”, “Advanced functional materials” and “Biofabrication” are the most productive and influential in AM scientific research.

The results and conclusions of this work can be used as indicators of trends in AM research and/or as prospects for future studies in this area.

Adopting additive manufacturing (AM) on a large-scale requires an adoption in company value chains. This may happen through product innovation and require interorganizational cooperation, but the value-adding potential of cooperation and application recognition is still poorly understood. This study aims to investigate the progress of AM adoption in innovation projects featuring AM application recognition and interorganizational cooperation in the value chain.

A multiple-case study was implemented in successful metallic AM adoption examples to increase the understanding of AM adoption in value chains. Primary data were collected through interviews and documents in three AM projects, and the data were analyzed qualitatively.

All three AM projects showed evidence of successful AM value chain adoption. Identifying the right application and the added value of AM within it were crucial starting points for finding new value chains. Interorganizational collaboration facilitated both value-based designs and experimentation with new supply chains. Thereby, the focal manufacturing company did not need to invest in AM machines. The key activities of the new value chain actors are mapped in the process of AM adoption.

The cases are set in a business-to-business context, which narrows the transferability of the results. As a theoretical contribution, this paper introduces the concept of AM value chain adoption. The value-adding potential of AM is identified, and the required value-adding activities in collaborative innovation are reported. As a practical implication, the study reveals how companies can learn of AM and adopt AM value chains without investing in AM machines. They can instead leverage relationships with other companies that have the AM knowledge and infrastructure.

This paper introduces AM value chain adoption as a novel, highly interactive phase in the industry-wide adoption of metallic AM. AM value chain adoption is characterized in multi-company collaboration settings, which complements the single-company view dominant in previous research. Theory elaboration is offered through merging technology adoption with external integration from the information processing view, emphasizing the necessity of interorganizational cooperation in AM value chain adoption. Companies can benefit each other during AM adoption, starting with identifying the value-creating opportunities and applications for AM.

Amongst various additive manufacturing (AM) techniques for realizing the complex metallic objects, weld-deposition (arc)-based directed energy AM technique is attaining more focus over commercially available powder bed fusion techniques. This is because of the capability of high deposition rates, high power and material utilization, simpler setup and less initial investment of arc-based AM. Nevertheless, realization of sudden overhanging features through arc-based weld-deposition techniques is still a challenging task because of the necessity of support structures. This paper aims to describe a novel methodology for producing complex metallic objects with sudden overhangs without using supports.

The realization of complex metallic objects with sudden overhangs (without using supports) is possible by reorienting the workpiece and/or deposition head at every instance using higher order kinematics (5-axis setup) to make sure the overhanging feature is in line to the deposition direction.

In the absence of universally applicable support mechanism, deposition of overhanging features remains one of the main challenges in AM. A separate support structure is often necessary for depositing the overhanging features. Small overhang features are usually possible by a little overextension from the previous layer. Nevertheless, deposition of large gradually varying overhangs and sudden overhangs with complex features without support structures is a challenging task in any AM process. This demands higher order kinematics which calls for inclined and/or orthogonal slicing and area filling.

The unique aspect of this paper is the identification of sudden overhang feature from a tessellated computer-aided design (.stl) file and generates an orthogonal tool path for deposition for sudden overhangs. An in-house MATLAB routine has been developed and presented for performing the same. This methodology helps in realization of sudden overhangs without use of supports. To validate proposed technique, various illustrative case studies have been taken up for deposition.

The purpose of this paper is to outline some key aspects such as material systems used, phenomenological and statistical process modeling, techniques applied to monitor the process and optimization approaches reported. All these need to be taken into account for the ongoing development of the SLM technique, particularly in health care applications. The outcomes from this review allow not only to summarize the main features of the process but also to collect a considerable amount of investigation effort so far achieved by the researcher community.

This paper reviews four significant areas of the selective laser melting (SLM) process of metallic systems within the scope of medical devices as follows: established and novel materials used, process modeling, process tracking and quality evaluation, and finally, the attempts for optimizing some process features such as surface roughness, porosity and mechanical properties. All the consulted literature has been highly detailed and discussed to understand the current and existing research gaps.

With this review, there is a prevailing need for further investigation on copper alloys, particularly when conformal cooling, antibacterial and antiviral properties are sought after. Moreover, artificial intelligence techniques for modeling and optimizing the SLM process parameters are still at a poor application level in this field. Furthermore, plenty of research work needs to be done to improve the existent online monitoring techniques.

This review is limited only to the materials, models, monitoring methods, and optimization approaches reported on the SLM process for metallic systems, particularly those found in the health care arena.

SLM is a widely used metal additive manufacturing process due to the possibility of elaborating complex and customized tridimensional parts or components. It is corroborated that SLM produces minimal amounts of waste and enables optimal designs that allow considerable environmental advantages and promotes sustainability.

The key perspectives about the applications of novel materials in the field of medicine are proposed.

The investigations about SLM contain an increasing amount of knowledge, motivated by the growing interest of the scientific community in this relatively young manufacturing process. This study can be seen as a compilation of relevant researches and findings in the field of the metal printing process.

The purpose of this study is, to compare laser-based additive manufacturing and subtractive methods. Laser-based manufacturing is a widely used, noncontact, advanced manufacturing technique, which can be applied to a very wide range of materials, with particular emphasis on metals. In this paper, the governing principles of both laser-based subtractive of metals (LB-SM) and laser-based powder bed fusion (LB-PBF) of metallic materials are discussed and evaluated in terms of performance and capabilities. Using the principles of both laser-based methods, some new potential hybrid additive manufacturing options are discussed.

Production characteristics, such as surface quality, dimensional accuracy, material range, mechanical properties and applications, are reviewed and discussed. The process parameters for both LB-PBF and LB-SM were identified, and different factors that caused defects in both processes are explored. Advantages, disadvantages and limitations are explained and analyzed to shed light on the process selection for both additive and subtractive processes.

The performance of subtractive and additive processes is highly related to the material properties, such as diffusivity, reflectivity, thermal conductivity as well as laser parameters. LB-PBF has more influential factors affecting the quality of produced parts and is a more complex process. Both LB-SM and LB-PBF are flexible manufacturing methods that can be applied to a wide range of materials; however, they both suffer from low energy efficiency and production rate. These may be useful when producing highly innovative parts detailed, hollow products, such as medical implants.

This paper reviews the literature for both LB-PBF and LB-SM; nevertheless, the main contributions of this paper are twofold. To the best of the authors’ knowledge, this paper is one of the first to discuss the effect of the production process (both additive and subtractive) on the quality of the produced components. Also, some options for the hybrid capability of both LB-PBF and LB-SM are suggested to produce complex components with the desired macro- and microscale features.

This study aims to develop and demonstrate a deposition framework for the implementation of a region-based adaptive slicing strategy for the Tungsten Inert Gas (TIG) welding-based additive manufacturing system. The present study demonstrates a deposition framework for implementing a novel region-based adaptive slicing strategy termed as Fast Interior and Accurate Exterior with Constant Layer Height (FIAECLH).

The mentioned framework has been developed by performing experiments using the design of experiments and analyzing the experimental data. Analysis results have been used to obtain the mathematical function to integrate customization in the process. The paper, in the end, demonstrates the FIAECLH framework for implementing region-based adaptive slicing strategy on the hardware level.

The study showcase a new way of implementing the region-based adaptive slicing strategy to arc-based metal additive manufacturing. The study articulating a new strategy for its implementation in all types of wire and arc additive manufacturing processes.

Wire-arc-based technology has the potential to deliver cost-effective solutions for metal additive manufacturing. The research on arc welding-based processes is being carried out in different dimensions. To deposit parts with complex geometry and better dimensional accuracy implementation of a novel region-based adaptive slicing strategy for the arc-based additive manufacturing process is an essential task. The successful implementation of an adaptive slicing strategy would ease the fabrication of complex geometry in less time. This paper accomplishes this need of implementing a region-based adaptive slicing strategy as no experimental investigation has been reported for the TIG-based additive manufacturing process.

Additive 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.

AM 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.

The 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.

This 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.

The 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.

This study highlights the demand for low-cost and high accuracy products through the design and development of new 3D printing technologies. Besides, significant progress has been made in this field. A comparative study helps to understand the latest development in materials and future prospect of this technology.

Nevertheless, a large amount of progress still remains to be made. While some of the works have focused on the performances of the materials, the rest have focused on the development of new methods and techniques in additive manufacturing.

This paper critically evaluates the current 3D printing technologies, including the development and optimizations made to the printing methods, as well as the printed objects. Meanwhile, previous developments in this area and contributions to the modern trend in manufacturing technology are summarized briefly.

The paper can be summarized in three sections. Firstly, the existing printing methods along with the frequently used printing materials, as well as the processing parameters, and the factors which influence the quality and mechanical performances of the printed objects are discussed. Secondly, the optimization techniques, such as topology, shape, structure and mechanical property, are described. Thirdly, the latest development and applications of additive manufacturing are depicted, and the scope of future research in the relevant area is put forward.

Additive manufacturing (AM) is revolutionizing the manufacturing industry due to several advantages and capabilities, including use of rapid prototyping, fabrication of complex geometries, reduction of product development cycles and minimization of material waste. As metal AM becomes increasingly popular for aerospace and defense original equipment manufacturers (OEMs), a major barrier that remains is rapid qualification of components. Several potential defects (such as porosity, residual stress and microstructural inhomogeneity) occur during layer-by-layer processing. Current methods to qualify AM parts heavily rely on experimental testing, which is economically inefficient and technically insufficient to comprehensively evaluate components. Approaches for high fidelity qualification of AM parts are necessary.

This review summarizes the existing powder-based fusion computational models and their feasibility in AM processes through discrete aspects, including process and microstructure modeling.

Current progresses and challenges in high fidelity modeling of AM processes are presented.

Potential opportunities are discussed toward high-level assurance of AM component quality through a comprehensive computational tool.

For metal additive manufacturing, metallic powders are usually produced by vacuum induction gas atomization (VIGA) through the breakup of liquid metal into tiny droplets by gas jets. VIGA is considered a cost-effective technique to prepare feedstock. In VIGA, the quality and the morphology of the produced particles are mainly controlled by the gas pressure used during powder production, keeping the setup configuration constant.

In VIGA process for metallic additive manufacturing feedstock preparation, the quality and morphology of the powder particles are mainly controlled by the gas pressure used during powder production.

In this study, Inconel-625 feedstock was produced using a supersonic nozzle in a close-coupled gas atomization apparatus. Powder size distribution (PSD) was studied by varying the gas pressure.

The nonmonotonic but deterministic relationships were observed between gas pressure and PSD. It was found that the maximum 15–45 µm percentage PSD, equivalent to 84%, was achieved at 29 bar Argon gas pressure, which is suitable for the LPBF process. Following on, the produced powder particles were used to print tensile test specimens via LPBF along XY- and ZX-orientations by using laser power = 475 W, laser scanning speed = 800 mm/s, powder layer thickness = 50 µm and hatch distance = 100 µm. The yield and tensile strengths were 9.45% and 13% higher than the ZX direction, while the samples printed in ZX direction resulted in 26.79% more elongation compared to XY-orientation.