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Data-driven Approach to Explore the Contribution of Process Parameters for Laser Powder Bed Fusion of a Ti-6Al-4V Alloy

  • Jeong Min Park (Department of 3D Printing Materials, Korea Institute of Materials Science (KIMS)) ;
  • Jaimyun Jung (Department of Materials AI & Big-Data, Korea Institute of Materials Science (KIMS)) ;
  • Seungyeon Lee (Department of 3D Printing Materials, Korea Institute of Materials Science (KIMS)) ;
  • Haeum Park (Department of 3D Printing Materials, Korea Institute of Materials Science (KIMS)) ;
  • Yeon Woo Kim (Department of 3D Printing Materials, Korea Institute of Materials Science (KIMS)) ;
  • Ji-Hun Yu (Department of 3D Printing Materials, Korea Institute of Materials Science (KIMS))
  • Received : 2024.04.02
  • Accepted : 2024.04.19
  • Published : 2024.04.28

Abstract

In order to predict the process window of laser powder bed fusion (LPBF) for printing metallic components, the calculation of volumetric energy density (VED) has been widely calculated for controlling process parameters. However, because it is assumed that the process parameters contribute equally to heat input, the VED still has limitation for predicting the process window of LPBF-processed materials. In this study, an explainable machine learning (xML) approach was adopted to predict and understand the contribution of each process parameter to defect evolution in Ti alloys in the LPBF process. Various ML models were trained, and the Shapley additive explanation method was adopted to quantify the importance of each process parameter. This study can offer effective guidelines for fine-tuning process parameters to fabricate high-quality products using LPBF.

Keywords

Acknowledgement

This work was supported by Principal R&D Project (PNK 9950) of the Korean Institute of Materials Science (KIMS), Basic Research Program (PICO960) of Korea Institute of Machinery and Materials (KIMM), and the project of "Development of powder and parts manufacturing technologies for 3D printing of high strength lightweight metals" through the Ministry of Trade, Industry, and Energy (Project No. 20013202).

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