Physics-Informed Machine Learning for Accurate Prediction of Temperature and Melt Pool Dimension in Metal Additive Manufacturing.

The temperature distribution and melt pool size have a great influence on the microstructure and mechanical behavior of metal additive manufacturing process. The numerical method can give relatively accurate results but is time-consuming and, therefore, unsuitable for in-process prediction. Owing to its remarkable capabilities, machine learning methods have been applied to predict melt pool size and temperature distribution. However, the success of traditional data-driven machine learning methods is highly dependent on the amount and quality of the training data, which is not always convenient to access. This article proposes a physics-informed machine learning (PIML) method, which integrates data and physics laws in the training parts, overcoming the problems of low speed and data availability. An artificial neural network constrained by the heat transfer equation and a small amount of labeled data is developed to predict the melt pool size and temperature distribution. Besides, the locally adaptive activation function is utilized to improve the prediction performance. The result shows that the developed PIML model can accurately predict the temperature and melt pool dimension under different scanning speeds with a small amount of labeled data, which shows significant potential in practical application.

A Review on Residual Stress in Metal Additive Manufacturing.

A new method for producing parts in the expanding sector is additive manufacturing. The appropriate name for three-dimensional (3D) printing is additive manufacturing because it produces the part layer by layer. Plastics and metals can be 3D printed in large quantities with the precise surface finish and feature quality needed in additive manufacturing. More specifically, direct metal sintering, direct energy deposition, and metal binder jetting are used in 3D printing. The computer-aided design model is completed when the powder bed has been successively scanned and lowered. The metal sintering process uses a powder bed with powder metal, and laser selectively melts a flattened bed of powder, which is done with roller with successive rolling of new layer on previous into desired shape before a new layer is pushed on top of the previous layer. As a result, the new layer has solidified on top of the earlier layer, causing the prior layer to melt back again. Because of the unique thermal cycle, this results in residual stress (RS). The unique thermal cycle of metal additive manufacturing is characterized by (1) rapid heating rate caused by high energy intensity and steep temperature gradients; (2) rapid solidification with high cooling rates because of the small volume of melt pool; and (3) melt back, which involves simultaneous melting of the top powder layer and re-melting of underlying previously solidified layers. The presence of RS in metal additive manufacturing (AM) creates difficulties that restrict the process's ability to produce parts at an industrial scale. During and after manufacturing, these forces may cause parts to distort and crack. This can be solved by heating the powder bed, which will lessen this type of issue. The causes, traits, and reduction of RS are the main topics of this review article. A number of conceptual approaches to reducing RS are addressed to provide some useful inspiration for creating a methodical RS balancing procedure for AM. These approaches are based on the state and future of the relevant techniques.

Ultrasonic field-assisted metal additive manufacturing (U-FAAM): Mechanisms, research and future directions.

Metal additive manufacturing (AM) is a disruptive technology that provides unprecedented design freedom and manufacturing flexibility for the forming of complex components. Despite its unparalleled advantages over traditional manufacturing methods, the existence of fatal issues still seriously hinders its large-scale industrial application. Against this backdrop, U-FAAM is emerging as a focus, integrating ultrasonic energy into conventional metal AM processes to harness distinctive advantages. This work offers an up-to-date, specialized review of U-FAAM, articulating the integrated modes, mechanisms, pivotal research achievements, and future development trends in a systematic manner. By synthesizing existing research, it highlights future directions in further optimizing process parameters, expanding material applicability, etc., to advance the industrial application and development of U-FAAM technology.

Physics-Informed Online Learning for Temperature Prediction in Metal AM.

In metal additive manufacturing (AM), precise temperature field prediction is crucial for process monitoring, automation, control, and optimization. Traditional methods, primarily offline and data-driven, struggle with adapting to real-time changes and new process scenarios, which limits their applicability for effective AM process control. To address these challenges, this paper introduces the first physics-informed (PI) online learning framework specifically designed for temperature prediction in metal AM. Utilizing a physics-informed neural network (PINN), this framework integrates a neural network architecture with physics-informed inputs and loss functions. Pretrained on a known process to establish a baseline, the PINN transitions to an online learning phase, dynamically updating its weights in response to new, unseen data. This adaptation allows the model to continuously refine its predictions in real-time. By integrating physics-informed components, the PINN leverages prior knowledge about the manufacturing processes, enabling rapid adjustments to process parameters, geometries, deposition patterns, and materials. Empirical results confirm the robust performance of this PI online learning framework in accurately predicting temperature fields for unseen processes across various conditions. It notably surpasses traditional data-driven models, especially in critical areas like the Heat Affected Zone (HAZ) and melt pool. The PINN's use of physical laws and prior knowledge not only provides a significant advantage over conventional models but also ensures more accurate predictions under diverse conditions. Furthermore, our analysis of key hyperparameters-the learning rate and batch size of the online learning phase-highlights their roles in optimizing the learning process and enhancing the framework's overall effectiveness. This approach demonstrates significant potential to improve the online control and optimization of metal AM processes.

3D Printing and Surface Engineering of Ti6Al4V Scaffolds for Enhanced Osseointegration in an In Vitro Study.

Ti6Al4V superalloy is recognized as a good candidate for bone implants owing to its biocompatibility, corrosion resistance, and high strength-to-weight ratio. While dense metal implants are associated with stress shielding issues due to the difference in densities, stiffness, and modulus of elasticity compared to bone tissues, the surface of the implant/scaffold should mimic the properties of the bone of interest to assure a good integration with a strong interface. In this study, we investigated the additive manufacturing of porous Ti6Al4V scaffolds and coating modification for enhanced osteoconduction using osteoblast cells. The results showed the successful fabrication of porous Ti6Al4V scaffolds with adequate strength. Additionally, the surface treatment with NaOH and Dopamine Hydrochloride (DOPA) promoted the formation of Dopamine Hydrochloride (DOPA) coating with an optimized coating process, providing an environment that supports higher cell viability and growth compared to the uncoated Ti6Al4V scaffolds, as demonstrated by the higher proliferation ratios observed from day 1 to day 29. These findings bring valuable insights into the surface modification of 3D-printed scaffolds for improved osteoconduction through the coating process in solutions.

A Review of the Vaporization Behavior of Some Metal Elements in the LPBF Process.

Metal additive manufacturing technology has developed by leaps and bounds in recent years; selective laser melting technology is a major form in metal additive manufacturing, and its application scenarios are numerous. For example, it is involved in many fields including aerospace field, automotive, mechanical processing, and the nuclear industry. At the same time, it also indirectly provides more raw materials for all walks of life in our country. However, during the selective laser melting process, due to the action of high-energy-density lasers, the temperature of most metal powders can reach above the vaporization temperature. Light metals with relatively low vaporization temperatures such as magnesium and zinc have more significant vaporization and other behaviors. At the same time, during the metal vaporization process, a variety of by-products are generated, which seriously affect the forming quality and mechanical properties of the workpiece, resulting in the workpiece quality possibly not reaching the expected target. This paper mainly interprets the metal vaporization behavior in the LPBF process and summarizes the international research progress and suppression methods for vaporization.

Effects of Low-Temperature Heat Treatment on Mechanical and Thermophysical Properties of Cu-10Sn Alloys Fabricated by Laser Powder Bed Fusion.

This study investigated the impact of low-temperature heat treatments on the mechanical and thermophysical properties of Cu-10Sn alloys fabricated by a laser powder bed fusion (LPBF) additive manufacturing (AM) process. The microstructure, phase structure, and mechanical and thermal properties of the LPBF Cu-10Sn samples were comparatively investigated under both the as-fabricated (AF) condition and after low-temperature heat treatments at 140, 180, 220, 260, and 300 °C. The results showed that the low-temperature heat treatments did not significantly affect the phase and grain structures of the Cu-10Sn alloys. Both pre- and post-treatment samples displayed consistent grain sizes, with no obvious X-ray diffraction angle shift for the α phase, indicating that atom diffusion of the Sn element is beyond the detection resolution of X-ray diffractometers (XRD). However, the 180 °C heat-treated sample exhibited the highest hardness, while the AF samples had the lowest hardness, which was most likely due to the generation of precipitates according to thermodynamics modeling. Heat-treated samples also displayed higher thermal diffusivity values than their AF counterpart. The AF sample had the longest lifetime of ~0.19 nanoseconds (ns) in the positron annihilation lifetime spectroscopy (PALS) test, indicating the presence of the most atomic-level defects.

Electroforming of Personalized Multi-Level and Free-Form Metal Parts Utilizing Fused Deposition Modeling-Manufactured Molds.

Adapting to the growing demand for personalized, small-batch manufacturing, this study explores the development of additively manufactured molds for electroforming personalized metal parts. The approach integrates novel multi-level mold design and fabrication techniques, along with the experimental procedures for the electroforming process. This work outlines design considerations and guidelines for effective electroforming in additively manufactured molds, successfully demonstrating the production of composite metal components with multi-level and free-form geometries. By emphasizing cost efficiency and part quality, particularly for limited-thickness metal components, the developed technique offers distinct advantages over existing metal additive manufacturing methods. This approach establishes itself as a flexible and durable method for metal additive manufacturing, expanding the scope of electroforming beyond traditional constraints such as thin-walled hollow structures, 2D components, and nanoscale applications.

Enabling the design of surgical instruments for under-resourced patients through metal additive manufacturing: ulnar shortening osteotomy as an example.

BACKGROUND: Ulnar shortening osteotomy (USO) has demonstrated good outcomes for patients with ulnar impaction syndrome. To minimize complications such as non-union, precise osteotomy and firm fixation are warranted. Despite various ulnar shortening systems have been developed, current technology does not meet all needs. A considerable portion of patients could not afford those designated USO systems. To tackle this challenge, our team reported successful results in standardized free-hand predrilled USO technique. However, it is still technical demanding and requires sufficient experience and confidence to excel. Therefore, our team designed an ulnar shortening system based on our free-hand technique principle, using metal additive manufacturing technology. The goal of this study is to describe the development process and report the performance of the system. METHODS: Utilizing metal additive manufacturing technology, our team developed an ulnar shortening system that requires minimal exposure, facilitates precise cutting, and allows for the easy placement of a 3.5 mm dynamic compression plate, available to patients at zero out-of-pocket cost. For performance testing, two surgeons with different levels of experience in ulnar shortening procedures were included: one fellow-trained hand and wrist surgeon and one senior resident. They performed ulnar shortening osteotomy (USO) using both the free-hand technique and the USO system-assisted technique on ulna sawbones, repeating each method three times. The recorded parameters included time-to-complete-osteotomy, total procedure time, chip diameter, shortening length, maximum residual gap, and deviation angle. RESULTS: For the hand and wrist fellow, with the USO system, the time-to-complete osteotomy was significantly reduced. (468.7 ± 63.6 to 260.0 ± 5 s, p < 0.05). Despite the preop goal was shortening 3 mm, the average shortening length was significantly larger in the free-hand group (5 ± 0.1; 3.2 ± 0.2 mm, p < 0.05). Both maximum residual gap and deviation angle reported no statistical difference between the two techniques for the hand surgeon. As for the senior resident, the maximum residual gap was significantly reduced, using the USO system (2.9 ± 0.8; 0.4 ± 0.4 mm, p = 0.02). Between two surgeons, significant larger maximum residual gap and deviation angle were noted on the senior resident doctor, in the free-hand technique group, but not in the USO system group. CONCLUSION: The developed USO system may serve as a valuable tool, aiding in reliable and precise cutting as well as fixation for patients undergoing ulnar shortening osteotomy with a 3.5 mm dynamic compression plate, even for less experienced surgeons. The entire process, from concept generation and sketching to creating the CAD file and final production, serves as a translatable reference for other surgical scenarios.

Corrosion Performance of Wire Arc Additive Manufacturing of Stainless Steel: A Brief Critical Assessment.

To enhance the products fabricated from wire arc additive manufacturing (WAAM) processes, it is very important to implement a critical assessment of the corrosion performance of additively manufactured stainless steel (SS) for the application of additive manufacturing parts widely used in industries. The common defects in metal additive manufacturing, which include porosity, poor surface finish, oxidation, environmental factor, residual stress, and microstructural defects, are known to significantly influence the corrosion behavior of WAAM-processed SS components prepared to be used under different corrosive and marine environments. This article reviews the recently published works on WAAM-processed SS and provides a critical overview method to improve the corrosion performance of SS components built with the WAAM processes. It also documents some significant factors that determine the corrosion resistance of WAAM-processed SS and identifies key areas for future work.

The Production of Three-Dimensional Metal Objects Using Oscillatory-Strain-Assisted Fine Wire Shaping and Joining.

Material shaping and joining are the two fundamental processes that lie at the core of many forms of metal manufacturing techniques, including additive manufacturing. Current metal additive manufacturing processes such as laser/e-beam powder bed fusion and Directed Energy Deposition predominantly use heat and subsequent melt-fusion and solidification to achieve shaping and joining. The energy efficiency of these processes is severely limited due to energy conversion losses before energy is delivered at the point of melt-fusion for shaping and joining, and due to losses through heat transfer to the surrounding environment. This manuscript demonstrates that by using the physical phenomenon of lowered yield stress of metals and enhanced diffusion in the presence of low amplitude high frequency oscillatory strain, metal shaping and joining can be performed in an energy-efficient way. The two performed simultaneously enable a metal additive manufacturing process, namely Resonance-Assisted Deposition (RAD), that has several unique capabilities, like the ability to print net-shape components from hard-to-weld alloys like Al6061 and the ability to print components with a very high aspect ratio. In this study, we show this process's capabilities by printing solid components using aluminum-based metal alloys.

Advances in Fatigue Performance of Metal Materials with Additive Manufacturing Based on Crystal Plasticity: A Comprehensive Review.

Using metal additive manufacturing processes can make up for traditional forging technologies when forming complex-shaped parts. At the same time, metal additive manufacturing has a fast forming speed and excellent manufacturing flexibility, so it is widely used in the aerospace industry and other fields. The fatigue strength of metal additive manufacturing is related to the microstructure of the epitaxially grown columnar grains and crystallographic texture. The crystal plasticity finite element method is widely used in the numerical simulation of the microstructure and macro-mechanical response of materials, which provides a strengthening and toughening treatment and can reveal the inner rules of material deformation. This paper briefly introduces common metal additive manufacturing processes. In terms of additive manufacturing fatigue, crystal plasticity simulations are summarized and discussed with regard to several important influencing factors, such as the microstructure, defects, surface quality, and residual stress.

[Critical Control Points and Case Studies in the Production of Metal Additive Manufacturing Medical Device].

The critical control points in the production quality management of metal additive manufacturing medical devices, including personnel, hardware, design and development, procurement control, production management and quality control are summarized from the perspective of supervision. The typical cases are analyzed to provide reference for medical device regulatory authorities and enterprises.

Simulation of 316L Stainless Steel Produced the Laser Powder Bed Fusion Process.

Additive manufacturing is increasingly being used in the production of parts of simple as well as complex shapes designed for various areas of industry. Prevention of errors in the production process is currently enabled using simulation tools that have the function of predicting possible errors and, at the same time, providing a set of information about the behaviour of the material in the metal additive manufacturing process. This paper discusses the simulation processes of 316L stainless steel produced using the laser powder bed fusion (L-PBF) process. Simulation of the printing process in the Simufact Additive simulation program made it possible to predict possible deformations and errors that could occur in the process of producing test samples. After analysing the final distortion already with compensation, the simulation values of maximum deviation -0.01 mm and minimum -0.13 mm were achieved.

Closed-loop recovery of molybdenum and value-added reuse of tungsten from alloy waste in additive manufacturing.

As metal additive manufacturing (MAM) technology is booming in the aerospace sector, alternatives to the traditional production methods of metals such as mining, processing, and refining with severe emissions are urgently needed. This study proposed a closed-loop route for efficient recovery of molybdenum (Mo) and value-added reuse of tungsten (W) from Cr-Co-Ni-Mo-W alloy waste in MAM. The results showed that the leaching efficiency of Mo and W reached 99.3% and 99.9%, respectively, using the dual chemical-physical means of mixed-alkali roasting and leaching by microwave heating, while the discharge of waste liquor containing Cr6+ was reduced. Leaching kinetic studies revealed that the metal leaching process was controlled by chemical reaction mechanism. Moreover, the 10%N1923 (primary amine)-5%TRPO (tri-alkyl phosphine oxide)-kerosene extraction system exhibited a synergistic extraction effect on Mo and W. After purification, Mo was recovered as Mo powder for MAM. Simultaneously, the recovered product of W, MnWO4, was applied as a photocatalytic material with excellent degradation of methylene blue dye. Ultimately, the proposed method obtained recovery efficiencies of 98.4% and 99.3% for Mo and W, respectively, achieving efficient and environmentally-friendly reuse of these key metals.

A Review of Computational Approaches to the Microstructure-Informed Mechanical Modelling of Metals Produced by Powder Bed Fusion Additive Manufacturing.

In the rapidly evolving field of additive manufacturing (AM), the predictability of part properties is still challenging due to the inherent multiphysics complexity of the technology. This results in time-consuming and costly experimental guess-and-check approaches for manufacturing each individual design. Through synthesising advancements in the field, this review argues that numerical modelling is instrumental in mitigating these challenges by working in tandem with experimental studies. Unique hierarchical microstructures induced by extreme AM process conditions- including melt pool patterns, grains, cellular-dendritic substructures, and precipitates-affect the final part properties. Therefore, the development of microstructure-informed mechanical models becomes vital. Our review of numerical studies explores various modelling approaches that consider the microstructural features explicitly and offers insights into multiscale stress-strain analysis across diverse materials fabricated by powder bed fusion AM. The literature indicates a growing consensus on the key role of multiscale integrated process-structure-property-performance (PSPP) modelling in capturing the complexity of AM-produced materials. Current models, though increasingly sophisticated, still tend to relate only two elements of the PSPP chain while often focusing on a single scale. This emphasises the need for integrated PSPP approaches validated by a solid experimental base. The PSPP paradigm for AM, while promising as a concept, is still in its infantry, confronting multifaceted challenges that require in-depth, multidisciplinary expertise. These challenges range from accounting for multiphysics phenomena (e.g., advanced laser-material interaction) and their interplay (thermo-mechanical and microstructural evolution for simulating Type II residual stresses), accurately defined assumptions (e.g., flat molten surface during AM or purely epitaxial solidification), and correctly estimated boundary conditions for each element of the PSPP chain up to the need to balance the model's complexity and detalisation in terms of both multiphysics and discretisation with efficient multitrack and multilayer simulations. Efforts in bridging these gaps would not only improve predictability but also expedite the development and certification of new AM materials.

Case Study of Large Three-Dimensional-Printed Slider with Conformal Cooling for High-Pressure Die Casting.

Metal three-dimensional (3D) printing technology brings several benefits to the field of high-pressure die casting of aluminum, which enhances its development. The associated conformal cooling application is already commonly used where there is a need to improve the quality of castings, increase tool life, or reduce the production cycle. However, will this technology withstand the production of a large part (∼270 × 270 × 200 mm), which will be used directly in the serial production of engine blocks? This article describes a slider with a conformal cooling case study, which was redesigned and manufactured using the laser powder bed fusion (L-PBF) method. After the slider was put into serial production of 1.0 TSI three-cylinder engine blocks, this tool was thoroughly monitored based on the temperature field by comparing the results of a simulation in SW ProCAST with reality, and furthermore examining the influence of the tool on the quality of castings. There was also an evaluation of repairs performed on the tool in the SKODA AUTO tool shop and the foundry. These data were compared with a serial tool. Finally, the costs to produce the slider in conventional and 3D-printed variants are compared with an outline of other possible steps for optimizing these costs. The study results show that relatively large parts can be printed and used in serial production even today. It was also confirmed that conformal cooling influenced improving tool life, and the number of repairs in SKODA AUTO production also decreased.

Comparison of Optical and Stylus Methods for Surface Texture Characterisation in Industrial Quality Assurance of Post-Processed Laser Metal Additive Ti-6Al-4V.

Additive manufacturing technologies enable lightweight, functionally integrated designs and development of biomimetic structures. They contribute to the reduction in material waste and decrease in overall process duration. A major challenge for the qualification for aerospace applications is the surface quality. Considering Ti-64 laser powder bed fusion (LPBF) parts, particle agglomerations and resulting re-entrant features are characteristic of the upper surface layer. Wet-chemical post-processing of the components ensures reproducible surface quality for improved fatigue behaviour and application of functional coatings. The 3D SurFin® and chemical milling treatments result in smoother surface finishes with characteristic properties. In order to characterise these surfaces, three methods for surface texture measurement (contact and non-contact) were applied, namely confocal microscopy, fringe projection and stylus profilometry. The aim of this work was to show their suitability for measurement of laser powder bed fusion as-built and post-processed surfaces and compare results across the evaluated surface conditions. A user-oriented rating of the methods, summarising advantages and disadvantages of the used instruments specifically and the methods in general, is provided. Confocal microscopy reaches the highest resolution amongst the methods, but measurements take a long time. The raw data exhibit large measurement artefacts for as-built and chemically milled conditions, requiring proper data post-processing. The stylus method can only capture 2D profiles and the measurement was restricted by particle agglomerations and craters. However, the method (process and instrument) is entirely standardised and handheld devices are inexpensive, making it accessible for a large group of users. The fringe projection method was the quickest and easiest regarding measurement and data post-processing. Due to large areal coverage, reproduction of location when performing repeat measurements is possible. The spatial resolution is lower than for confocal microscopy but is still considered sufficiently high to characterise the investigated surface conditions.

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.

Anisotropy Evaluation and Defect Detection on Laser Power Bed Fusion 316L Stainless Steel.

Because of rapid heating, cooling, and solidification during metal additive manufacturing (AM), the resulting products exhibit strong anisotropy and are at risk of quality problems from metallurgical defects. The defects and anisotropy affect the fatigue resistance and material properties, including mechanical, electrical, and magnetic properties, which limit the applications of the additively manufactured components in the field of engineering. In this study, the anisotropy of laser power bed fusion 316L stainless steel components was first measured by conventional destructive approaches using metallographic methods, X-ray diffraction (XRD), and electron backscatter diffraction (EBSD). Then, anisotropy was also evaluated by ultrasonic nondestructive characterization using the wave speed, attenuation, and diffuse backscatter results. The results from the destructive and nondestructive methods were compared. The wave speed fluctuated in a small range, while the attenuation and diffuse backscatter results were varied depending on the build direction. Furthermore, a laser power bed fusion 316L stainless steel sample with a series of artificial defects along the build direction was investigated via laser ultrasonic testing, which is more commonly used for AM defect detection. The corresponding ultrasonic imaging was improved with the synthetic aperture focusing technique (SAFT), which was found to be in good agreement with the results from the digital radiograph (DR). The outcomes of this study provide additional information for anisotropy evaluation and defect detection for improving the quality of additively manufactured products.