Additive manufacturing (AM) is one of the recently studied research areas, due to its ability to eliminate different subtractive manufacturing limitations, such as difficultly in fabricating complex parts, material wastage, and numbers of sequential operations. Laser-powder bed fusion (L-PBF) AM for SS316L is known for complex part production due to layer-by-layer deposition and is extensively used in the aerospace, automobile, and medical sectors. The process parameter selection is crucial for deciding the overall quality of the SS316L build component with L-PBF AM. This review critically elaborates the effect of various input parameters, i.e., laser power, scanning speed, hatch spacing, and layer thickness, on various mechanical properties of AM SS316L, such as tensile strength, hardness, and the effect of porosity, along with the microstructure evolution. The effect of other AM parameters, such as the build orientation, pre-heating temperature, and particle size, on the build properties is also discussed. The scope of this review also concerns the challenges in practical applications of AM SS316L. Hence, the residual stress formation, their influence on the mechanical properties and corrosion behavior of the AM build part for bio implant application is also considered. This review involves a detailed comparison of properties achievable with different AM techniques and various post-processing techniques, such as heat treatment and grain refinement effects on properties. This review would help in selecting suitable process parameters for various human body implants and many different applications. This study would also help to better understand the effect of each process parameter of PBF-AM on the SS316L build part quality.

In this article, the significance of additive manufacturing techniques in the production of vehicle parts over the past several years is highlighted. It indicates the industries and scientific sectors in which these production techniques have been applied. The primary manufacturing methods are presented based on the materials used, including both metals and non-metals. The authors place their primary focus on additive manufacturing techniques employing metals and their alloys. Within this context, they categorize these methods into three main groups: L-PBF (laser-powder bed fusion), sheet lamination, and DED (directed energy deposition) techniques. In the subsequent stages of work on this article, specific examples of vehicle components produced using metal additive manufacturing (MAM) methods are mentioned.

Machine learning (ML) is one of the artificial intelligence tools which uses past data to learn the relationship between input and output and helps to predict future trends. Powder bed fusion additive manufacturing (PBF-AM) is extensively used for a wide range of applications in the industry. The AM process establishment for new material is a crucial task with trial-and-error approaches. In this work, ML techniques have been applied for the prediction of the density of PBF-AM. Density is the most vital property in evaluating the overall quality of the AM building part. The ML techniques, namely, artificial neural network (ANN), K-nearest neighbor (KNN), support vector machine (SVM), and linear regression (LR), are used to develop a model for predicting the density of the stainless steel (SS) 316L build part. These four methods are validated using R-squared values and different error functions to compare the predicted result. The ANN and SVM model performed well with the R-square value of 0.95 and 0.923, respectively, for the density prediction. The ML models would be beneficial for the prediction of the process parameters. Further, the developed ML model would also be helpful for the future application of ML in additive manufacturing.

Selective laser melting (SLM) is an additive manufacturing technique. It allows elements with very complex geometry to be produced using metallic powders. A geometry of manufacturing elements is based only on 3D computer-aided design (CAD) data. The metal powder is melted selectively layer by layer using an ytterbium laser. This paper contains the results of porosity and microhardness analysis made on specimens manufactured during a specially prepared process. Final analysis helped to discover connections between changing hatching distance, exposure speed and porosity. There were no significant differences in microhardness and porosity measurement results in the planes perpendicular and parallel to the machine building platform surface.

The present paper aims to analyze the microstructure, microhardness, tensile properties, and low cycle fatigue (LCF) behavior of friction stir welded (FSW) butt joints. The material used in this study was the 5 mm thick 5083 H111 aluminum alloy sheet. Butt joints of AA 5083 H111 were manufactured at different operating parameters of the FSW process. The effect of the welding parameters on microstructure, microhardness, and tensile properties was investigated. Based on microstructure analysis and strength tests, the most favorable parameters of the FSW process were settled on the point of view of weld quality. Then, LCF tests of base material and friction stir welded specimens made of 5083 H111 were carried out for the examined welded samples under selected friction stir welding parameters. The process of low-cycle fatigue of 5083 H111 aluminum alloy was characterized by cyclic hardening for both: base material and FSW joint. It was revealed by a decrease in the width of the hysteresis loop with the simultaneous significant increase in the values of the range of stress. It was determined that fatigue cracks are initiated by cyclic slip deformation due to local stress concentration from the surface in the corner of the samples for the base material and the heat-affected zone for FSW joints. For all tested strain amplitudes, the fatigue crack propagation region is characterized by the presence of fatigue striation with secondary cracks.

The present paper aims to analyze the influence of process parameters (tool traverse speed and tool rotational speed) on the macrostructure, microhardness, and mechanical properties of dissimilar friction stir welded (FSW) butt joints. Nine combinations of FSW parameters welded joints of aluminum alloys 7020-T651 and 5083-H111 were characterized. Plates in 5 mm thickness were welded using the FSW method as dissimilar joints with three values of tool rotation parameters (400, 800, and 1200 rpm) and three welding speeds (100, 200, 300 mm/min). The macroscopic observations revealed various shapes of the stir zone and defects resulting from excess and insufficient heat input. Microfractographic analysis and tensile test results showed that the samples made with the FSW parameters of 800 rpm and 200 mm/min had the best strength properties: UTS = 303 MPa, YS = 157 MPa, and A = 11.6 %. Moreover, for all welds at welding speed 100 mm/min, the joint efficiency reached 95%.