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The growing demand for Nitinol alloy parts in industries like automotive and aerospace underscores the need for optimizing machining parameters to improve both product quality and cost efficiency. Key factors such as spindle speed (L), feed rate (f), and depth of cut (t) significantly influence the machining process. Important performance indicators, including material removal rate (MRR), tool wear (TW), and surface roughness (Ra), are used to assess the effectiveness of the process. This paper uses a fuzzy logic-based utility function to identify the optimal machining conditions for dry turning Nitinol 56.

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Utility Function Approach Integrated with Fuzzy for Optimization in Dry Turning of Nitinol 56

  • 会议论文

  • 发表日期：

    2025年

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  • Soni Kumari,
  • Dev Sureja,
  • Kumar Abhishek,
  • Gunjan Kumar

摘要

The growing demand for Nitinol alloy parts in industries like automotive and aerospace underscores the need for optimizing machining parameters to improve both product quality and cost efficiency. Key factors such as spindle speed (L), feed rate (f), and depth of cut (t) significantly influence the machining process. Important performance indicators, including material removal rate (MRR), tool wear (TW), and surface roughness (Ra), are used to assess the effectiveness of the process. This paper uses a fuzzy logic-based utility function to identify the optimal machining conditions for dry turning Nitinol 56.