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<p>In the field of materials engineering, achieving enhanced efficiency in duplex stainless steel machining is a critical pursuit. This study examines the application of advanced cryogenic milling techniques coupled with predictive modeling. This research focuses on elevating the efficiency of duplex stainless steel machining through the innovative integration of advanced cryogenic milling techniques and predictive modeling like back-propagation neural network and genetic algorithm. Duplex stainless steel, known for its superior corrosion resistance and mechanical properties, presents machining challenges due to its inherent toughness. The study pioneers the application of cryogenic milling, leveraging extremely low temperatures to enhance tool life, reduce wear, and improve overall machining performance. The study reveals a 25% increase in tool life and a 20% reduction in wear compared to conventional methods using cryogenic milling. Predictive modeling enhanced machining performance, optimizing material removal rates by 15% while extending tool longevity. The proposed alloy’s yield strength of 770&#xa0;MPa significantly surpasses other alloys, demonstrating superior mechanical performance. This research contributes to the ongoing evolution of machining technologies, fostering a paradigm shift toward precision, sustainability, and enhanced efficiency in the fabrication of critical components from duplex stainless steel.</p>

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Enhanced Efficiency in Duplex Stainless Steel Machining through Advanced Cryogenic Milling Techniques and Predictive Modeling

  • 期刊论文

  • 发表日期：

    2025年3月18日

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  • Tarun Kumar Kotteda,
  • Venkata Sanyasi Seshendra Kumar Karri,
  • Praveen Barmavatu,
  • Abilash Radhakrishnan,
  • Sushant Mohan Patil

摘要

In the field of materials engineering, achieving enhanced efficiency in duplex stainless steel machining is a critical pursuit. This study examines the application of advanced cryogenic milling techniques coupled with predictive modeling. This research focuses on elevating the efficiency of duplex stainless steel machining through the innovative integration of advanced cryogenic milling techniques and predictive modeling like back-propagation neural network and genetic algorithm. Duplex stainless steel, known for its superior corrosion resistance and mechanical properties, presents machining challenges due to its inherent toughness. The study pioneers the application of cryogenic milling, leveraging extremely low temperatures to enhance tool life, reduce wear, and improve overall machining performance. The study reveals a 25% increase in tool life and a 20% reduction in wear compared to conventional methods using cryogenic milling. Predictive modeling enhanced machining performance, optimizing material removal rates by 15% while extending tool longevity. The proposed alloy’s yield strength of 770 MPa significantly surpasses other alloys, demonstrating superior mechanical performance. This research contributes to the ongoing evolution of machining technologies, fostering a paradigm shift toward precision, sustainability, and enhanced efficiency in the fabrication of critical components from duplex stainless steel.