Additive Manufacturing Research Research Articles

Comparison of STP and TP Modes of Wire and Arc Additive Manufacturing of Aluminum–Magnesium Alloys: Forming, Microstructures and Mechanical Properties

Aluminum–magnesium (Al–Mg) alloys, known for their lightweight properties, are extensively utilized and crucial in the advancement of wire and arc additive manufacturing (WAAM) for direct high-quality printing—a focal point in additive manufacturing research. This study employed 1.2 mm ER5356 welding wire as the raw material to fabricate two sets of 30-layer thin-walled structures. These sets were manufactured using two distinct welding modes, speed-twin pulse (STP) and twin pulse (TP). Comparative evaluations of the surface quality, microstructures, and mechanical properties of the two sets of samples indicated that both the STP and TP modes were suitable for the WAAM of Al–Mg alloys. Analyses of grain growth in the melt pools of both sample sets revealed a non-preferential grain orientation, with a mixed arrangement of equiaxed and columnar grains. The STP mode notably achieved a refined surface finish, a reduced grain size, and a slight increase in tensile strength compared to the TP mode. From the comparison of the tensile data at the bottom, middle, and top of the two groups of samples, the additive manufacturing process in the STP mode was more stable.

Transferability Analysis of Data-Driven Additive Manufacturing Knowledge: A Case Study Between Powder Bed Fusion and Directed Energy Deposition

Abstract Data-driven research in additive manufacturing (AM) has gained significant success in recent years. This has led to a plethora of scientific literature emerging. The knowledge in these works consists of AM and artificial intelligence (AI) contexts that haven't been mined and formalized in an integrated way. Moreover, no tools or guidelines exist to support data-driven knowledge transfer from one context to another. As a result, data-driven solutions using specific AI techniques are being developed and validated only for specific AM process technologies. There is a potential to exploit the inherent similarities across various AM technologies and adapt the existing solutions from one process or problem to another using AI, such as transfer learning (TL). We propose a three-step knowledge transferability analysis framework in AM to support data-driven AM knowledge transfer. As a prerequisite to transferability analysis, AM knowledge is featured into identified knowledge components. The framework consists of pre-transfer, transfer, and post-transfer steps to accomplish knowledge transfer. A case study is conducted between two flagship metal AM processes: laser powder bed fusion (LPBF) and directed energy deposition (DED). The relatively mature LPBF is the source while the less developed DED is the target. We show successful transfer at different levels of the data-driven solution, including data representation, model architecture, and model parameters. The pipeline of AM knowledge transfer can be automated in the future to allow efficient cross-context or cross-process knowledge exchange.

Progress and Opportunities for Machine Learning in Materials and Processes of Additive Manufacturing.

In recent years, there has been widespread adoption of machine learning (ML) technologies to unravel intricate relationships among diverse parameters in various additive manufacturing (AM) techniques. These ML models excel at recognizing complex patterns from extensive, well-curated datasets, thereby unveiling latent knowledge crucial for informed decision-making during the AM process. The collaborative synergy between ML and AM holds the potential to revolutionize the design and production of AM-printed parts. This review delves into the challenges and opportunities emerging at the intersection of these two dynamic fields. It provides a comprehensive analysis of the publication landscape for ML-related research in the field of AM, explores common ML applications in AM research (such as quality control, process optimization, design optimization, microstructure analysis, and material formulation), and concludes by presenting an outlook that underscores the utilization of advanced ML models, the development of emerging sensors, and ML applications in emerging AM-related fields. Notably, ML has garnered increased attention in AM due to its superior performance across various AM-related applications. It is envisioned that the integration of ML into AM processes will significantly enhance 3D printing capabilities across diverse AM-related research areas.

Experimental and statistical study on the effect of process parameters on the quality of continuous fiber composites made via additive manufacturing

Ongoing research in additive manufacturing towards structural and industrial application has led to the use of commingled roving as a manufacturing feedstock for printing high fiber volume fraction composites. The prospects of using this technology for high performance applications necessitates the need for a comprehensive experimental investigation into the effects of processing parameters on the quality of an additively manufactured composite printed from commingled roving feedstock. In this work, transverse flexure and void fraction matrix pyrolysis testing are both performed to evaluate composite quality. The transverse flexure test is a testing approach that evaluates the quality of the interfacial fiber-matrix bond while the void fraction test estimates the void content in the printed composite. A full observational study consisting of 27 different test combinations is done to investigate the effects of three different process parameters namely, temperature, pressure, and print speed across three different levels. Composite samples were made from commingled roving of E-glass and amorphous PET using an in-house built continuous fiber composite digital manufacturing system. Least squares regression analysis is performed to study the main, interaction and quadratic effects of process parameters. A statistical regression model having an R2 adjusted value of 80.1% is generated from the transverse flexure study, which is used to explain main and interaction effects and also predict performance. Response surface plots are also generated and are used to optimize process parameters which can subsequently be of help in scaling up composite manufacturing. Results show that all three process parameters are highly statistically significant at the 0.01 level of significance. Pressure * Temperature and Pressure * Printspeed are significant interaction terms. Pressure plays a weightier role when print speed is increased or temperature is decreased as it closes more voids that would ordinarily have been introduced because of drop in polymer melt viscosity. Micrographic analysis is also performed.

Evaluation of the segregation in printed mono-sized Al-In alloy droplets

Monotectic alloys, with a focus on lightweight and multifaceted aluminum-indium alloys, possess extensive applications and considerable potential for growth within high-tech sectors. This study addresses a crucial gap within additive manufacturing research pertaining to monotectic alloys, a matter of significance in the context of Industry 4.0. We investigate the application of Uniform Metal Droplet Printing Technology (UMDPT) to address the segregation issue prevalent during the solidification process of these alloys, an impediment compromising their resilience and longevity. The research not only advocates for the use of UMDPT in producing monotectic alloys, but also offers valuable insights into the mechanisms of segregation inhibition, thereby broadening the understanding of additive manufacturing technology. Experimental results indicate that this technology can efficaciously inhibit the segregation of the indium-rich secondary phase during the solidification of the aluminum-indium alloy. The conducted experiments utilized droplets at 1073 K with a nozzle diameter of 500 μm and demonstrated a uniform dispersion of the secondary phase, with a size of 0.5 μm and a variation coefficient of 0.375. This groundbreaking research outcome bears considerable implications for further advancements in this domain and fosters the evolution of more efficient manufacturing methodologies.

Detection of defects during laser-powder interaction by acoustic emission sensors and signal characteristics

Acoustic Emission (AE) sensing is an in-situ real-time nondestructive monitoring method proposed for Additive Manufacturing (AM) to detect defects such as cracks. Previous AE research in AM mainly focused on developing algorithms to automatically detect the defects from AE signals without understanding the physical mechanisms or the signal characteristics that could be used as identifiers. We study AE signals during a laser spot welding on a powder bed to clearly distinguish between different physical mechanisms using their signal characteristics. We identified specific signals associated with 1) tensile cracks from cooling, 2) a powder effect on the substrate, and 3) sudden thermal expansion of the substrate. We used the spectral ratio between high frequency (70–150 kHz) and low frequency (10–40 kHz) spectral amplitudes in the frequency domain to classify and differentiate the source types. We found that porosity due to insufficient energy density did not produce detectable AE signals. Using a ball drop calibration technique, we used AE signals to estimate the absolute sizes of the tensile cracks. Crack sizes ranged from 40 μm to 1 mm and were in general agreement with scanning electron microscope images of the fractures. We performed a line scanning test and successfully validated its potential for the application. Our findings provide a basic understanding of AE signal characteristics in AM, as well as the practical parameters used to separate the signal types.

Ultrasonic testing for metal additive manufacturing: Experience with new course development

Metal additive manufacturing (AM) has brought about the need for nondestructive evaluation (NDE) methods to assess part quality. AM processes result in complex microstructures, porosity, material texture, and residual stresses all of which may vary spatially throughout the part. Thus, knowledge of ultrasonic NDE methods to characterize materials is relevant to the AM community. To address this challenge, a new graduate-level course entitled “Ultrasound for Metal Additive Manufacturing,” was created at the University of Nebraska-Lincoln. The course followed a cognitive-situative blended learning approach to give students practical ultrasonics training regardless of prior acoustics background. The theory introduced key topics including: the general wave equation, plane wave solutions, waves in isotropic solids, impact of material anisotropy, role of material interfaces, reflection and transmission, surface waves, scattering, dispersion, material dissipation, and scattering attenuation. A series of laboratory experiments allowed students to learn: experimental setups, signal processing, transducer properties and selection, beam mapping, wave speed and attenuation measurements, and diffuse-field measurements. Finally, each student developed a project incorporating ultrasound measurements into their individual AM research. Their findings were included in research articles, conference presentations, and PhD dissertations. This presentation will describe the course design, successes, and recommendations for future implementations.

(Invited) An Overview of Electrochemistry Application to Additive Manufacturing

Additive manufacturing (AM) is the process of creating three-dimensional (3D) objects from digital models through the sequential deposition of material in layers. This talk will highlight how researchers have used electrochemical research in additive manufacturing and will provide insights into how technology can be exploited to formulate novel microstructures and optimize the manufacturing process. Electrochemical 3D printing is a relatively new form of AM that creates metallic structures through the electrochemical reduction of metal ions from solutions onto conductive substrates. It involves localized electrochemical deposition of metals combined with additive manufacturing principles to achieve Electrochemical Additive Manufacturing (ECAM). The talk will also focus on the formulation of metal precursor inks to produce novel metallic microstructures and nanoalloys containing multiple metals. These inks are used with AM techniques to fabricate 2D and 3D printed conductive structures directly onto a substrate. Examples include aligned nickel nanowires over large areas, which provide opportunities to produce structures with enhanced anisotropic electrical and magnetic properties. Nanoalloy films printed using metal precursor inks have a variety of important applications involving local control of alloy composition in AM part. Examples include the facile formation of layered nanostructures and electrical conductivity with oxidative stability. The talk will conclude with current research on electropolishing of AM parts. AM while capable of producing complex-shaped metal parts with intricate internal geometries and lattice structures struggles to make parts with the smooth surface finish required for many applications. Polishing interior surfaces inaccessible to traditional surface polishing methods is a challenge. Electropolishing is increasingly being used as a post-treatment option for metal AM parts due to its non-contact nature and ability to finish complex internal features.

Wood-based additive manufacturing: Current methodologies

Wood-based additive manufacturing (AM), some examples of which are called 3D printing, is a promising technology for reducing the environmental impact of manufacturing and increasing the sustainability of the construction industry. This review paper provides an overview of various AM methods, including commonly used wood-based techniques and the mechanical and physical properties of their products. The paper also discusses challenges related to precision and surface finish in wood-based AM and identifies areas for future research, including the effects of wood species, particle size, and processing parameters on the mechanical properties and dimensional stability of wood-based AM products. The review concludes by discussing the potential implications of wood-based AM for sustainable materials and the construction industry, along with recommendations for future research such as the development of new wood-based AM techniques and exploration of new applications for this technology. This paper provides valuable insights into the current state of wood-based AM research and its potential to revolutionize sustainable manufacturing practices.

Medical Additive Manufacturing: Challenges and Features

Over the past 20 years, Medical Additive Manufacturing has been immensely developed and become an essential part of Contemporary healthcare. In the past, additive manufacturing was only utilized to develop basic anatomical models, but as technology evolved, it became more straightforward for researchers to produce complex medical devices. Medical additive manufacturing is a promptly emerging field with the competence to print living tissues and organs for transplantation and produce personalized implants and prostheses with astounding precision and accuracy. The ability of 3D printing to produce products that precisely match a patient’s unique anatomy has significant benefits for medicine, including better patient outcomes. Additive manufacturing is often employed in the orthopedic and dentistry fields to design, build, or produce parts specifically for the patient’s exact and ideal fit. Additionally, it is extensively being utilized to produce surgical equipment and customized anatomical models for pre-surgical planning. This allows surgeons to practice complex procedures on a replica of the patient’s anatomy, improving surgical outcomes and reducing the risk of complications. Experts are exploring the possibility of utilizing 3D printing techniques for developing innovative methods to administer medication, which could improve treatment effectiveness and patient well-being. Additionally, these advancements have contributed immensely to creating human organs through bio-printing technology; a progress that has the potential to revolutionize organ transplants as they exist today by reducing dependence on donors. Another imminent advancement is surgical robotics using robots created through 3D printing procedures working side by side with medical experts thus improving patient outcomes and decreasing risks associated with traditional surgery techniques. Ongoing research and development promise even more groundbreaking applications in the future. This research article gives an attempt at medical additive manufacturing research now, then, and in the future.

Direct additive manufacturing of metal parts for automotive applications

Additive manufacturing or three-dimensional (3D) printing offers tremendous opportunities for the automotive industry to reduce vehicle weight and improve vehicle performance through consolidating parts, tailoring material properties, enabling multifunctional components, and simplifying manufacturing processes. However, additive manufacturing research for direct manufacturing of automotive components is limited, partially because of the sheer volume of automotive production. In this paper, we explore the potential of direct manufacturing of metallic vehicle components using additive manufacturing coupled with the generative design approach. Using a radar mounting bracket as an example, we show that desired part strength and safety performance can be achieved with 42 % weight reduction and simplified manufacturing and assembly process. A production cost analysis was also conducted based on two mainstream additive manufacturing systems. The result suggests that the cost of metal powder is the limiting factor for wider adoption of additive manufacturing in the automotive industry.

A Survey on Process Modelling, Innovation, Design, and Material Characterisation in Additive Manufacturing

The unique design freedom offered by additive manufacturing (AM) technologies enables engineers to develop more innovative products with relatively lower costs within a shorter period of processing time in comparison with conventional manufacturing methods. On the other hand, the unique capabilities of AM have created a platform for researchers to combine several engineering methods with the new manufacturing technique to grow industrial applications as well as resolve the existing issues with AM processes. Understanding the research values that AM offers academic environments, this paper performs a systematic survey on AM-related research topics in the fields of mechanical engineering and materials science that have attracted much attention from research teams over the last few years. These topics, namely process modelling in AM, innovative research in AM, generative design by AM, material characterisation in AM processes, and finally, design for additive manufacturing (DfAM), are notably investigated through this study.

Profiles in Materials Science: Osaka University’s Anisotropic Design and Additive Manufacturing Research Center

Abstract Osaka University established the Center for Dissimilar Custom Design and Additive Manufacturing Research & Development to connect research-based AM with industrial implementation. It recently established another specialized AM research group at its new Anisotropic Design & Additive Manufacturing Research Center, which will further develop AM technology via an industry-academia collaboration. In this article, Hideyuki Kanematsu talks with Takayoshi Nakano, director of Osaka University’s newest research hub, about the center’s goals as well as the latest prospects for AM technology in Japan.

Modeling Materials Coextrusion in Polymers Additive Manufacturing.

Material extrusion additive manufacturing enables us to combine more materials in the same nozzle during the deposition process. This technology, called material coextrusion, generates an expanded range of material properties, which can gradually change in the design domain, ensuring blending or higher bonding/interlocking among the different materials. To exploit the opportunities offered by these technologies, it is necessary to know the behavior of the combined materials according to the materials fractions. In this work, two compatible pairs of materials, namely Polylactic Acid (PLA)-Thermoplastic Polyurethane (TPU) and Acrylonitrile Styrene Acrylate (ASA)-TPU, were investigated by changing the material fractions in the coextrusion process. An original model describing the distribution of the materials is proposed. Based on this, the mechanical properties were investigated by analytical and numerical approaches. The analytical model was developed on the simplified assumption that the coextruded materials are a set of rods, whereas the more realistic numerical model is based on homogenization theory, adopting the finite element analysis of a representative volume element. To verify the deposition model, a specific experimental test was developed, and the modeled material deposition was superimposed and qualitatively compared with the actual microscope images regarding the different deposition directions and material fractions. The analytical and numerical models show similar trends, and it can be assumed that the finite element model has a more realistic behavior due to the higher accuracy of the model description. The elastic moduli obtained by the models was verified in experimental tensile tests. The tensile tests show Young's moduli of 3425 MPa for PLA, 1812 MPa for ASA, and 162 MPa for TPU. At the intermediate material fraction, the Young's modulus shows an almost linear trend between PLA and TPU and between ASA and TPU. The ultimate tensile strength values are 63.9 MPa for PLA, 35.7 MPa for ASA, and 63.5 MPa for TPU, whereas at the intermediate material fraction, they assume lower values. In this initial work, the results show a good agreement between models and experiments, providing useful tools for designers and contributing to a new branch in additive manufacturing research.

Laser-Based Additive Manufacturing of Magnesium Alloys for Bone Tissue Engineering Applications: From Chemistry to Clinic

Metallic biomedical implants are made from materials such as stainless steel, titanium, magnesium, and cobalt-based alloys. As a degradable biometal, magnesium (Mg) and its alloys are becoming more popular for applications in bone tissue engineering. Mg-based alloys have been found to be biocompatible, bioabsorbable, and bioactive, allowing them to be used as orthopedic implants with a low Young’s modulus. Computer-aided design can be used to design scaffolds with intricate porous structures based on patient-specific anatomical data. These models can be materialized rapidly and with reasonably acceptable dimensional accuracy by additive manufacturing (AM) techniques. It is known that lasers are the most widely investigated energy source for AM’ed Mg, as they offer some distinct advantages over other forms of energy. Recent studies have focused on developing biodegradable Mg scaffolds by using laser-based AM techniques. In this paper, we aim to review the recent progress of laser-based AM for Mg alloys and survey challenges in the research and future development of AM’ed Mg scaffolds for clinical applications.

In-Space Additive Manufacturing: A Review

Abstract Manufacturing or repairing parts on-site, high geometric freedom, and feedstock efficiency have long been regarded as nascent capabilities of additive manufacturing (AM) technologies. Researchers aim to adopt these capabilities for the future of space exploration, and polymer AM demonstrations in space were achieved in 2014; however, methods to process metals and other materials are needed. This paper provides a comprehensive review of AM research tested on reduced-gravity platforms from academia and industry across the globe. In addition, complementary processes and technologies under development are summarized. Reports from the literature are categorized by established AM process terminology and processed material. Lastly, alternatives to enabling metal AM in space are discussed, and knowledge gaps are presented.

An overview on the use of operations research in additive manufacturing

Additive Manufacturing (AM) is a disruptive production technology that challenges many well-established, conventional practices in Operations and Supply Chain Management decisions. Consequently, new context-specific decision problems have appeared in this area, while existing decision problems must be adapted or extended to this context. In this overview, these decision problems in AM are highlighted and classified, describing the different decision in an unified manner and citing the underlying OR techniques that have been applied to solve them. The aim of the paper is that, by presenting an overview of the AM-related problems in a systematic, OR- or Decision-Making-centred (rather than technology-centred) manner, the OR community can become more aware of this stream of research and thus be more active and contribute with some high-quality work. Open research challenges, as well as avenues for future research are also discussed.

Compressive behavior of Co-Cr-Mo radially graded porous structures under as-built and heat-treated conditions

Additive manufacturing research is continuously growing, and this field requires a full improvement of the capability and reliability of the processes involved. Of particular interest is the study of complex geometries production, such as lattice structures, which may have a potentially huge field of application, especially for biomedical products. In this work, the powder bed fusion technique was utilized to manufacture lattice structures with defined building angles concerning the build platform. A biocompatible Co-Cr-Mo alloy was used. Three different types of elementary cell geometry were selected: Face Centered Cubic, Diagonal, and Diamond. These cells were applied to the radially oriented lattice structures to evaluate the influence of their orientation in relation to the sample and the build platform. Moreover, heat treatment was carried out to study its influence on microstructural properties and mechanical behavior. Microhardness was measured, and compressive tests were performed to detect load response and to analyse the fracture mechanisms of these structures. The results show that the mechanical properties are highly influenced by the cell orientation in relation to the building direction and that the properties can be further tuned via HT. The favorable combination of mechanical properties and biocompatibility suggests that Co-Cr-Mo lattices may represent an optimal solution to produce customized metal implants.

Effects of laser surface modification on stainless steel 316L thin annular discs under radial and cartesian scans

Lasers direct use on metals allows treatment of localized surfaces, without affecting nearby material or the body of the piece. Depending on the expected result, laser surface treatments are classified into hardening, texturing, alloying, coating, and melting. Using the latter is possible to modify the microstructure, dissolve precipitates, and increase hardness and wear resistance, among other applications depending on the material and the parameters used. In this work, it is proposed to empirically study the Laser Surface Melting (LSM) technique on 316L stainless steel annular discs, to evaluate the influence of laser scanning pattern on the results of the laser treatment. The considered scanning patterns correspond to a Cartesian, the most used pattern in the LSM process, also known as “zigzag”, and a Radial pattern, previously proposed in Additive Manufacturing research, which moves the laser in a cylindrical way. The main contribution of this work is to introduce the variable of the scanning pattern in LSM studies, besides, generating a complete characterization of laser treatment on 316L stainless steel annular discs. The results show that, under the same conditions, the variation of the scanning pattern produces a meaningful change in the stress state of the specimen and its deformation after treatment. The main results of LSM treatment were an increase in crystallite size and a decrease in dislocation density, a state of compression, a slight hardening in the melted layer, and a decrease in toughness. This knowledge can be used to encourage new scanning patterns in this field.

Effect of N2- and CO2-containing shielding gases on composition modification and carbonitride precipitation in wire arc additive manufactured grade 91 steel

Additive manufacturing (AM) represents a promising technique to fabricate metallic alloys with greater control of the resulting material features as compared to traditional manufacturing routes. Recently, there is greater interest in AM research on 9 wt% Cr ferritic/martensitic (F/M) steels, which are commonly studied for use in the nuclear energy industry. This research aims to prove that wire arc AM can manufacture F/M steels with adequate mechanical properties in multiple processing atmospheres and aims to study how shielding gas composition can be leveraged during fabrication to induce specific precipitation pathways. The effect of shielding gas composition on MX (M=Nb and/or V, XC and/or N) carbonitride precipitation in a 9 wt% Cr ferritic/martensitic (F/M) steel alloy known as Grade 91 was studied using N2 and CO2 gas additions to an inert Ar shielding gas atmosphere during wire arc AM. The N and C atoms present in the processing atmospheres were absorbed into the melt pools during fabrication. Due to their differing affinities for precipitate-forming reactions, the varying levels of C and N between the samples contributed to differences in final carbonitride composition and morphologies. Such precipitate behavior is of interest as carbonitrides have been shown to contribute to increased mechanical performance. This increased performance was studied via electron microscopy and tested for strength, ductility, and fracture properties.