- [English]
- Optimization of VIGA Process Parameters for Power Characteristics of Fe-Si-Al-P Soft Magnetic Alloy using Machine Learning
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Sung-Min Kim, Eun-Ji Cha, Do-Hun Kwon, Sung-Uk Hong, Yeon-Joo Lee, Seok-Jae Lee, Kee-Ahn Lee, Hwi-Jun Kim
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J Powder Mater. 2022;29(6):459-467. Published online December 1, 2022
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DOI: https://doi.org/10.4150/KPMI.2022.29.6.459
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Abstract
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Soft magnetic powder materials are used throughout industries such as motors and power converters. When manufacturing Fe-based soft magnetic composites, the size and shape of the soft magnetic powder and the microstructure in the powder are closely related to the magnetic properties. In this study, Fe-Si-Al-P alloy powders were manufactured using various manufacturing process parameter sets, and the process parameters of the vacuum induction melt gas atomization process were set as melt temperature, atomization gas pressure, and gas flow rate. Process variable data that records are converted into 6 types of data for each powder recovery section. Process variable data that recorded minute changes were converted into 6 types of data and used as input variables. As output variables, a total of 6 types were designated by measuring the particle size, flowability, apparent density, and sphericity of the manufactured powders according to the process variable conditions. The sensitivity of the input and output variables was analyzed through the Pearson correlation coefficient, and a total of 6 powder characteristics were analyzed by artificial neural network model. The prediction results were compared with the results through linear regression analysis and response surface methodology, respectively.
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Citations
Citations to this article as recorded by 
- Microstructure, Magnetic Properties, and Performance of Fe-6.5Si Soft Magnetic Core Produced by Laser Powder Bed Fusion
Ji Sang Yoon, Yeon Woo Kim, Gyu Hyun Park, Youk Jin Kim, Sang Heon Lee, Jeong Seok Kim, Sung Ho Yu, Jeong Min Park Journal of Powder Materials.2026; 33(3): 177. CrossRef
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