Metal Additive Manufacturing Parts Research Articles

Multi-laser scan assignment and scheduling optimization for large-scale metal additive manufacturing

Metal Additive Manufacturing (AM) has attracted significant attention in various industry sectors for large-scale fabrication. However, the limited fabrication efficiency has hindered its practical implementation. In comparison to traditional methods of tuning process parameters, concurrent AM equipped with multiple independently driven lasers is a more promising technique recently developed for the efficient fabrication of large metal parts. To maximize fabrication efficiency while ensuring quality for a multi-laser AM processes, an optimization problem is proposed in this work for multi-laser scanning plan, including scan vector assignment and scheduling. The goal is to minimize the makespan while considering factors that may affect the quality of metal AM parts as constraints. Specifically, the constraints associated with heat-affected zones and the user-specified single-laser scanning area are considered. The optimization model is solved by Deep Reinforcement Learning (DRL), offering the flexibility to include or exclude considerations for different quality/process requirements. Two case studies demonstrate the application of DRL models considering different sets of constraints and compare their performance with two baseline scheduling methods in terms of fabrication efficiency and violation of quality constraints. In addition, the impact of the laser number on operational improvement and the computational cost of the DRL model is also studied.

Electrochemical polishing with glycol-based electrolyte of the curved internal channels fabricated via laser powder bed fusion

Electrochemical polishing (ECP) is used to process metal additive manufacturing parts with poor surface qualities arising from powder adhesion, spheroidal effect, and step effect during forming. Conventional ECP uses stationary acid-based solutions and very low current densities, which makes it challenging to efficiently polish complex-shaped internal channels. Typically, an oxide layer forms in the conventional aqueous-based electrolyte, which prevents uniform dissolution and consequently deteriorates surface quality. In this study, we proposed a modified ECP method for polishing curved internal channels in laser powder bed fusion (LPBF) 316 L stainless steel (SS) specimens using a high-speed flow of a NaCl–ethylene glycol (EG) solution at low current densities. During electrochemical tests, LPBF 316LSS specimens did not exhibit passivation in the NaCl–EG solution, and the current efficiency was high at low current densities (i < 4 A·cm−2). The reaction mechanism of ECP LPBF 316LSS in the NaCl–EG solution was clarified by observing the experimental phenomena and testing the composition of the reaction products. The ECP experiments showed that the decrease of roughness value is directly related to the charge. A small roughness value can also be obtained at low current densities (i < 2 A·cm−2). Finally, S-shaped curved holes with a diameter of Φ3 mm were efficiently polished using a flexible cathode in the NaCl–EG solution. In the case of an aperture increase rate of only about 7 %, it would only take 400 s to drastically reduce the surface roughness value Sa from 12.73 to 12.94 μm to 2.16– 2.43 μm.

Research on an Online Monitoring Device for the Powder Laying Process of Laser Powder Bed Fusion.

Improving the quality of metal additive manufacturing parts requires online monitoring of the powder bed laying procedure during laser powder bed fusion production. In this article, a visual online monitoring tool for flaws in the powder laying process is examined, and machine vision technology is applied to LPBF manufacture. A multiscale improvement and model channel pruning optimization method based on convolutional neural networks is proposed, which makes up for the deficiencies of the defect recognition method of small-scale powder laying, reduces the redundant parameters of the model, and enhances the processing speed of the model under the premise of guaranteeing the accuracy of the model. Finally, we developed an LPBF manufacturing process laying powder defect recognition algorithm. Test experiments show the performance of the method: the minimum size of the detected defects is 0.54 mm, the accuracy rate of the feedback results is 98.63%, and the single-layer laying powder detection time is 3.516 s, which can realize the effective detection and control of common laying powder defects in the additive manufacturing process, avoids the breakage of the scraper, and ensures the safe operation of the LPBF equipment.

Selective Surface Feature Electropolishing of Additively Manufactured 316L Using Pulse Electrochemistry

Electrochemical finishing of metallic surfaces is a scalable, relatively cost-effective technique that is also versatile. One of the main detractions is that the current distribution is uneven and unspecific, often leading to a lack of shape retention and, if it goes too far, inducing corrosion. Pulsing the electrical input creates an unsteady state during electropolishing, controlling the current distribution across the part. The pulse wave prevention of general non-uniform current distribution across the entire geometry instead produces local non-uniformities in the current distribution at given surface features. Many pulse electropolishing parameters can be varied to target individual surface features, including the electrolyte, pulse height, pulse width (equally and unequally distributed), time of polishing as well as the overall waveform.Additive manufacturing (AM) can produce unique, complex structures rapidly. The fast local melting of metal AM parts cool quickly due to the small area, causing unique microstructures, pores, and larger surface roughness compared to cast. AM microstructures change mechanical and chemical properties, such as strength and corrosion, compared to traditionally manufactured parts. Variations in build parameters and composition creates a complicated, feature dependent, corrosion response. By polishing the surface, some of the features, namely the corrosion resistance, wear, and aesthetics can be standardized and enhanced.In this work, we explore the underlying electrochemistry that governs pulse electropolishing. We show that controlling the electrolyte with environmentally benign chemicals ultimately influences the part dimensions that can be polished, the ability to polish, and the propensity to corrode. The pulse height, pulse width (Fig. 1), and total charge passed have an impact on different surface feature removal. We will demonstrate impact of the pulse parameters on the polishing of additively manufactured stainless steel. We go beyond simple planar geometry and apply our understanding to larger scale complex geometry parts, while maintaining near-net shape and minimizing mass loss. Figure 1

(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.

Mass finishing of additively manufactured Ti6Al4V parts: An investigation of surface finish dependency on build orientation and processing conditions

Poor surface finish of as-built metal Additive Manufacturing (AM) remains a key challenge in fabricated parts. Metal AM parts typically require postprocessing to improve surface finish before application. Furthermore, different surface orientations and scanning strategies in Powder-Bed-Fusion (PBF) metal AM are prone to result in non-uniform surface roughness across different surfaces of a part. In recent years, Mass Finishing (MF) technologies, such as Centrifugal Disc Finishing (CDF), are gaining popularity in improving AM surfaces due to its fixture-free, batch-processing, and relatively low costs. There is a critical need to study the surface finish dependency on AM build orientation and MF processing conditions. In this study, Ti6Al4V ASTM-E8b tensile bars were fabricated in 45⁰ and 90⁰ orientation via Laser Powder Bed Fusion (L-PBF) to investigate the effects of CDF processing conditions on upward facing surface (up-skin), downward facing surface (down-skin), and side facing surface (side-skin). The surface roughness evolution on each type of surface were collected via laser scanning profilometry. It was found that both processing speed and processing time of CDF were statistically significant factors in improving AM surface roughness, however, processing time had higher impact. Furthermore, different build orientation demonstrated different surface roughness reduction rate and material removal rate. It was found that side-skin had the highest average roughness reduction, and the down-skin exhibited the least roughness reduction. In addition, this study found that the surface with the highest initial surface roughness (down-skin) had the least material removal rate, and that the highest material removal rate was observed in surface with higher periodicity (side-skin). Findings from this study will help the AM community in decision-making of CDF conditions to prevent over-finishing and under-finishing. In addition, the investigation of surface evolution dependency on AM build orientation can further improve the understanding of key mechanisms of AM + MF hybrid manufacturing system.

A Review of the Residual Stress Generation in Metal Additive Manufacturing: Analysis of Cause, Measurement, Effects, and Prevention.

Metal additive manufacturing (AM) is capable of producing complex parts, using a wide range of functional metals that are otherwise very difficult to make and involve multiple manufacturing processes. However, because of the involvement of thermal energy in the fabrication of metallic AM parts, residual stress remains one of the major concerns in metal AM. This residual stress has negative effects on part quality, dimensional accuracy, and part performance. This study aims to carry out a comprehensive review and analysis of different aspects of residual stress, including the causes and mechanisms behind the generation of residual stress during metal AM, the state-of-the-art measurement techniques for measuring residual stress, various factors influencing residual stress, its effect on part quality and performance, and ways of minimizing or overcoming residual stress in metal AM parts. Residual stress formation mechanisms vary, based on the layer-by-layer deposition mechanism of the 3D printing process. For example, the residual stress formation for wire-arc additive manufacturing is different from that of selective laser sintering, direct energy deposition, and powder bed fusion processes. Residual stress formation mechanisms also vary based on the scale (i.e., macro, micro, etc.) at which the printing is performed. In addition, there are correlations between printing parameters and the formation of residual stress. For example, the printing direction, layer thickness, internal structure, etc., influence both the formation mechanism and quantitative values of residual stress. The major effect residual stress has on the quality of a printed part is in the distortion of the part. In addition, the dimensional accuracy, surface finish, and fatigue performance of printed parts are influenced by residual stress. This review paper provides a qualitative and quantitative analysis of the formation, distribution, and evolution of residual stress for different metal AM processes. This paper also discusses and analyzes both in situ and ex situ measurement techniques for measuring residual stress. Microstructural evolution and its effect on the formation of residual stress are analyzed. Various pre- and post-processing techniques used to countermeasure residual stress are discussed in detail. Finally, this study aims to present both a qualitative and quantitative analysis of the existing data and techniques in the literature related to residual stress, as well as to provide a critical analysis and guidelines for future research directions, to prevent or overcome residual stress formation in metal AM processes.

Enabling rapid X-ray CT characterisation for additive manufacturing using CAD models and deep learning-based reconstruction

Metal additive manufacturing (AM) offers flexibility and cost-effectiveness for printing complex parts but is limited to few alloys. Qualifying new alloys requires process parameter optimisation to produce consistent, high-quality components. High-resolution X-ray computed tomography (XCT) has not been effective for this task due to artifacts, slow scan speed, and costs. We propose a deep learning-based approach for rapid XCT acquisition and reconstruction of metal AM parts, leveraging computer-aided design models and physics-based simulations of nonlinear interactions between X-ray radiation and metals. This significantly reduces beam hardening and common XCT artifacts. We demonstrate high-throughput characterisation of over a hundred AlCe alloy components, quantifying improvements in characterisation time and quality compared to high-resolution microscopy and pycnometry. Our approach facilitates investigating the impact of process parameters and their geometry dependence in metal AM.

Ultra-precision surface finishing and feature generation on metal additive manufactured components with controlled tool path design

Metal additive manufacturing (AM) is a rapidly emerging technology gaining significant attention in industries. The intrinsic advantages of design freedom and mass customization establishes the dominance of AM over conventional methods. In the present scenario, nanofinished metallic surfaces with micro-features forms major requirement in industries for controlling reflectivity, fluid retention capacity and frictional performance of surfaces. However, the existing metal AM technology is incapable to produce high resolution microfeatures over the part surfaces due to restriction in laser spot diameter. Moreover, the fabricated metal AM parts are far different from nominal CAD design model due to form deviations and the presence of excessive surface irregularities. The aforementioned challenges lower the efficacy of metal AM surfaces in optical and tribological applications. Thus, a secondary surface post-treatment method is inevitable to overcome aforementioned limitations. Therefore, the present study proposes a hybrid method combining metal AM with ultra-precision surface finishing to achieve nanofinished features on customized metal AM components. The unmelted powder particles and other surface irregularities were eliminated through multiple finishing passes which ultimately yielded a surface finish of ∼ 49 nm. Based on designed tool path, micro-feature generation was successfully accomplished on metal AM surface with minimal deviations in the geometric profile of the feature.

Laser-induced breakdown spectroscopy and stoichiometry to identify various types of defects in metal-additive manufacturing parts

The purpose of this study is to use LIBS and SVM combined with the stoichiometry to quickly distinguish the defect categories of AM components.

Influence of Laser Additive Manufacturing and Laser Polishing on Microstructures and Mechanical Properties of High-Strength Maraging Steel Metal Materials

To increase the surface quality of the high-strength maraging steel metal materials, a new method of executing the additive manufacturing process and subtraction polishing process of maraging steel metal materials was studied. The mechanical properties of maraging steel metal materials before and after laser powder bed fusion (LPBF) polishing were compared and analyzed. The influence of laser parameters on the formability of high-strength MS metal materials was studied, with MS additive parts successfully prepared. The initial surfaces had roughness values of 6.198–7.92 μm. The metal additive manufacturing parts were polished with double laser beams. Confocal microscopy, scanning electron microscopy, and X-ray diffraction were used to obtain the microstructure and phase composition of the microstructures. The microhardness of high-strength maraging forming parts by using a microhardness tester and the mechanical properties were analyzed. The results showed that the surface roughness was considerably reduced to lengthen the service life of the high-strength MS metal materials from an initial roughness of Sa = 6.3 μm to Sa = 0.98 μm, with the surface hardness increased and the martensite content decreased after using double-laser-beam polishing.

Defect and Distortion in Powder Bed Fusion of Metal Additive Manufacturing Parts

One of the state-of-the-art technologies for metal fabrication is laser powder bed fusion, which includes the following printing techniques: selective laser melting, selective laser sintering, direct metal laser sintering, and electron beam melting. This work examines defect formation in laser powder bed fusion, predominately focusing on selective laser melting. It also explores recent research findings on defect formation and classification and analyzes various internal defects, such as porosity, lack of fusion, balling, and solidification cracking. The influence of process parameters on defect formation and the effect of defects on mechanical properties are analyzed. This review also discusses defect inspection technologies (melt pool, scan path, and slice monitoring), defect mitigation strategies (online detection, process parameters, and numerical simulation), and their applications in additive manufacturing, such as laser powder bed fusion. This review would aid manufacturers in determining the root cause of defect formation and developing inspection technologies and mitigation strategies.

Investigation of the influence of process interruption on mechanical properties of metal additive manufacturing parts

Fabrication methods of metals range from traditional subtractive methods to the new and emerging additive manufacturing technologies. As expected, these different metal fabrication and processing methods have a significant impact on the material structure and mechanical properties of final products. While the impact of the manufacturing process on the mechanical properties of metals is well understood for traditional manufacturing methods, the relationship between the additive manufacturing process and product characteristics is quite complex and still an ongoing research topic. Accordingly, many research studies on the material structure and mechanical properties of parts produced using additive manufacturing have been conducted in recent years. However, current literature considers ideal operating conditions while neglecting to consider the impact of printing process interruption on metal additive manufacturing parts. Additive manufacturing processes rely on continuous layer by layer printing of material, with strict melting and solidification requirements. When the printing process is interrupted, thermal dynamics governing binding strength and defect generation within layers are disturbed. It is expected that additive manufacturing process interruptions impact layer binding, which in turn jeopardizes the development of uniform microstructures and mechanical properties of metal parts. Accordingly, in this paper the impact of process interruption on the microstructure and mechanical properties of titanium samples printed using Wire Arc Additive Manufacturing (WAAM) is investigated. Various tests on the sample specimens are conducted including: Acoustic Resonance testing, Nanomechanical testing, X-ray Computed Tomography, and Ultrasonic nondestructive testing (NDT). The results indicate that additive manufacturing process interruption results in serious defects such as porosities and cracking that impact the mechanical properties of additive manufacturing metal parts.

(Digital Presentation) Effects of Surface Finish on the Corrosion Performance of Additively Manufactured Metals

Metal additive manufacturing (AM) is becoming a transformative technology in the manufacturing industry. The as-built surfaces produced by metal AM are very different compared to wrought material, typically resulting in very rough surfaces that have different corrosion properties. There are a large number of studies that have attempted to understand the corrosion response of metal AM. However, these studies are typically performed on materials that have been printed on a single machine. As a result, there are significant inconsistencies in the literature due to the high variability in the quality of parts manufactured on different machines. We will present work that compares the corrosion response of AM 316L stainless steel (SS) that has been printed on multiple machines. Our results have shown there is significant variability observed in the corrosion performance of metal AM parts built on different machines and within a single build plate. The observed corrosion performance is likely affected by the stability of the passive film, chemical segregation, and microstructure of the surface. We also propose that surface finishing of AM 316L SS reduces the part-to-part variations observed in the corrosion performance of the material printed on different machines and within a single build plate.This talk will discuss the corrosion properties of AM 316L SS, A20x (AM aluminum alloy), and Ti-6Al-4V parts produced by direct metal laser sintering (DMLS). The majority of our work focused on understanding the susceptibility to localized corrosion of metal additively manufactured materials with respect to build machine, surface roughness, and build angle. As a result, we also examined the corrosion performance of 316L SS built on a single instrument as we varied the build parameters. Conventional electrochemical corrosion experiments were used to characterize corrosion performance, including open circuit potential, potentiostatic electrochemical impedance spectroscopy, and potentiodynamic polarization scans. White light interferometry, optical profilometry, scanning electron microscopy, and energy-dispersive X-ray spectroscopy were utilized to characterize the surface of the samples.

Examination of quality assurance method for metal additive manufacturing by X-ray computed tomography

There are various technical issues in aiming at the productization of metal additive manufacturing parts. One of them is the issue of quality assurance. In particularly, it is necessary to thoroughly consider the inspection method and assurance method for internal structures and complex shapes.

Defect identification of metal additive manufacturing parts based on laser-induced breakdown spectroscopy and machine learning

Defect identification of metal additive manufacturing parts based on laser-induced breakdown spectroscopy and machine learning

A Survey of Mechanical Property Variability of Additively Manufactured Metals

Abstract Metal additive manufacturing (AM) processes, such as laser powder bed fusion, allow for the realization of parts with features and characteristics that cannot be achieved with traditional material removal manufacturing technologies. Despite impressive applications of metal AM parts in demanding aerospace applications, there remain concerns about the variability in mechanical properties of parts made with these processes. This variability leads to concerns by program managers and other decision-makers and a reluctance to potentially use metal AM parts in applications where they would otherwise be beneficial. Some of this reluctance might be assuaged if the actual property variability was better known. Here, we examine the literature of metal AM tensile property data to quantify variability in the metal AM process and compare it to the variability found in traditionally fabricated metals. It is shown that the variability in tensile material properties is somewhat similar between AM metals and conventional metals.

Method for Rapid Modeling of Distortion in Laser Powder Bed Fusion Metal Additive Manufacturing Parts

The simulation and modeling of part-level distortion and residual stress in diverse metal additive manufacturing (AM) geometries has great potential to enable the rapid adoption of this technology in engineering design. Moreover, the use of additive manufacturing component libraries (CLs) offer a computationally efficient means of quantifying these part-level defects resultant from AM processing. We report on how the individual simulations of simple shapes, potential entries in a CL, can be superimposed to provide an indication of distortion and residual stresses in complex geometries. Laser powder bed fusion AM was used to construct test geometries of varied shapes and their combinations in the form of CLs in an effort to characterize location-dependent and feature-dependent distortion distributions. Blue light scanning was used to experimentally measure 3D distortions in order to investigate the interaction between the component shapes and local boundary conditions. Overall, part-level distortions were highly dependent on test component geometry, local boundary conditions, and shape combination. Commercial finite element software was used to verify experimental trends and to make predictions of distortion. The use of CLs resulted in over 20 times savings in computational cost while reproducing overall trends in distortion for test geometry assemblies. Therefore, it is anticipated that the use of CLs for L-PBF AM geometries has demonstrated potential to facilitate efficient simulations of full component AM assemblies, thereby reducing the need for costly trial-and-error-type experimental analysis.

Automated inclusion and porosity analysis of metal additive manufacturing parts

Automated inclusion and porosity analysis of metal additive manufacturing parts

Heterogeneous Aspects of Additive Manufactured Metallic Parts: A Review

Metal additive manufacturing (MAM) is an emerging technology to produce complex end-use metallic parts. To adopt MAM for manufacturing numerous engineering parts used in critical applications, a thorough understanding of the relationship between the complex thermal cycles in MAM and the unique heterogeneous microstructures of MAM parts need to be established. This review article provides a comprehensive overview of the evolution of heterogeneous microstructures in MAM parts, including melt pool boundaries, heterogeneous grain structure, sub-grain cellular structure, matrix supersaturation, segregation, phase transformation, oxides formation, and texture. The evolution of residual stresses and the anisotropy in MAM parts and the post-MAM heat treatment effects on the microstructural evolution are also discussed. This review covers the microstructural aspects of most engineering materials in particular steels, high entropy alloys, aluminum alloys, titanium alloys, nickel-base superalloys, and copper alloys, with a primary focus on the parts manufactured using selective laser melting, direct energy deposition, and electron beam melting processes.