Process Parameter Optimization Framework for the Selective Laser Melting of Hastelloy X Alloy Considering Defects and Solidification Crack Occurrence

Abstract

Recent years have witnessed increasing demand for selective laser melting (SLM) in practical applications; however, determining the appropriate process parameter range remains challenging. In this study, a framework was developed to determine the appropriate process parameter range considering the occurrence of defects and cracks by conducting a single-track test and thermal elastoplastic analysis. Keyholing, balling, and the residual unmelted regions were considered defects. The occurrence of solidification cracking, which is predominant in the SLM of solution-strengthened Ni-based alloys, was considered. Using the proposed framework, we could fabricate a part with largely no defects or cracks, except for the edges, under the determined optimal process parameters.

Novel Calibration Strategy for Validation of Finite Element Thermal Analysis of Selective Laser Melting Process Using Bayesian Optimization

“…Thus, it is not feasible to use such a 3D model for the calibration procedure with iterative simulations even though Bayesian optimization can significantly reduce the number of iterations. However, a 3D thermal analysis can be desirable to understand the temperature distribution better and combine the results of thermal simulation with other simulations (such as thermal stress analysis [9], thermal elastoplastic analysis [7,8], and grain growth simulation [2]). Consequently, a rational process is to use the 2D model to calibrate the parameters and use the calibrated parameters to simulate the 3D model.…”

“…Through the process, the material temperature periodically and rapidly rises and falls with melting and solidification with transformations. Such a thermal history affects the characteristic microstructure [1,2] and material properties [3,4], and it can also generate defects such as pores [5] and microcracks [6][7][8], and can cause distortion [9].…”

“…The acquisition function can balance between sampling at the points where the modeled objective function is low and exploring the areas that have not yet been modeled, resulting in efficient parameter optimization. For example, using Bayesian optimization, Kitano et al [7,8] have successfully found an optimal laser irradiation conditions to avoid defects and cracks in SLMed nickel superalloys. Shiraiwa et al [23] efficiently determined the heat source parameters in welding simulation using Bayesian optimization.…”

Melt Pool Shape Evaluation by Single-Track Experiments and Finite-Element Thermal Analysis: Balling and Lack of Fusion Criteria for Generating Process Window of Inconel738LC

“…According to the past studies, D / W and D / t have been used to identify keyholing and lack of fusion, respectively [ 2 , 11 , 16 , 17 ]. Note that t is the powder layer thickness.…”

“…Kitano et al conducted single-track experiments using the Ni-based alloy of Hastelloy X and used the keyholing identification by D / W > 1.0. The lack of fusion has been identified using the criterion D < t [ 2 , 11 , 17 ]. The meaning of D / t < 1 is clear; the powder layer insufficiently melts by the single-track experiment.…”