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<p>This study uses self-developed system designs to present a new approach for magnetic field-assisted machining (MFAM) of Ti–6Al–4V alloys. Using finite element analysis (FEA) , the system was designed to enhance magnetic flux density. Various magnet configurations were examined, identifying an optimal spacing of 0.5 mm for maximizing flux density. Subsequently, a system prototype was fabricated. To optimize the MFAM process for grinding Ti–6Al–4V alloys, an optimization strategy was adopted, combining the robust design method, gray relational analysis, and a fuzzy inference system. The control parameters considered in this study were wheel speed, depth of cut, wheel cross-feed rate, and table rate. Using a multiobjective optimization approach, the performance of the MFAM system was evaluated and compared against conventional grinding (CG). The results revealed a remarkable improvement in grinding performance with MFAM. Specifically, the MFAM system yielded an 8.29% reduction in grinding force, a 25.93% decrease in grinding temperature, and a 23.64% improvement in surface roughness. Furthermore, the MFAM-processed surfaces exhibited an enhanced appearance. These experimental findings unequivocally demonstrate the superiority of the MFAM system over CG in grinding Ti–6Al–4V alloys. This innovative technology holds immense promise for revolutionizing the efficiency of titanium alloy grinding in industrial applications.</p>

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Development of a magnetic field-assisted grinding system and multi-objective optimization of titanium alloy grinding processes

  • 期刊论文

  • 发表日期：

    2025年7月10日

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  • Wei-Tai Huang,
  • Yu-Hsiang Cheng,
  • Jinn-Tsong Tsai,
  • Wen-Hsien Ho

摘要

This study uses self-developed system designs to present a new approach for magnetic field-assisted machining (MFAM) of Ti–6Al–4V alloys. Using finite element analysis (FEA) , the system was designed to enhance magnetic flux density. Various magnet configurations were examined, identifying an optimal spacing of 0.5 mm for maximizing flux density. Subsequently, a system prototype was fabricated. To optimize the MFAM process for grinding Ti–6Al–4V alloys, an optimization strategy was adopted, combining the robust design method, gray relational analysis, and a fuzzy inference system. The control parameters considered in this study were wheel speed, depth of cut, wheel cross-feed rate, and table rate. Using a multiobjective optimization approach, the performance of the MFAM system was evaluated and compared against conventional grinding (CG). The results revealed a remarkable improvement in grinding performance with MFAM. Specifically, the MFAM system yielded an 8.29% reduction in grinding force, a 25.93% decrease in grinding temperature, and a 23.64% improvement in surface roughness. Furthermore, the MFAM-processed surfaces exhibited an enhanced appearance. These experimental findings unequivocally demonstrate the superiority of the MFAM system over CG in grinding Ti–6Al–4V alloys. This innovative technology holds immense promise for revolutionizing the efficiency of titanium alloy grinding in industrial applications.