<p>Difficult-to-machine materials are widely used in medical, aerospace, and automotive applications due to their high strength, wear resistance, and corrosion resistance. However, their high strength, brittleness, and poor thermal conductivity often lead to significant surface cracks, excessive residual stress, and roughness during machining, failing to meet application standards for cutting and grinding surfaces. Cutting and grinding forces are primary factors influencing machining accuracy and workpiece quality, yet effective control methods for these forces across various difficult-to-machine materials remain limited. However, the current research on grinding force prediction models for various difficult-to-machine materials lacks a corresponding review to provide unified guidance. Based on this, this study addresses this gap by analyzing and summarizing cutting and grinding force models for these materials. First, cutting and grinding force models for various difficult-to-machine materials are classified and reviewed. Based on material characteristics and machining performance, difficult-to-machine materials are categorized as super alloys, hard brittle materials, and composite materials, with the error ranges of corresponding force models summarized. Subsequently, the application of these models in machining processes is discussed, identifying the main factors affecting cutting and grinding forces and examining how machining methods influence these forces. Additionally, based on model application, the most widely recognized and applicable force model for various materials is identified. Finally, potential future research directions are proposed to address current challenges in grinding force research. This study aims to provide theoretical guidance and technical support for predicting cutting and grinding forces in difficult-to-machine materials to enhance surface quality.</p>

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Force models for difficult-to-machine materials in cutting and grinding: a comparative assessment

  • Xianggang Kong,
  • Jiachao Hao,
  • Min Yang,
  • Wei Song,
  • Teng Gao,
  • Mingzheng Liu,
  • Xin Cui,
  • Benkai Li,
  • Xiao Ma,
  • Shouhai Chen,
  • Changhe Li

摘要

Difficult-to-machine materials are widely used in medical, aerospace, and automotive applications due to their high strength, wear resistance, and corrosion resistance. However, their high strength, brittleness, and poor thermal conductivity often lead to significant surface cracks, excessive residual stress, and roughness during machining, failing to meet application standards for cutting and grinding surfaces. Cutting and grinding forces are primary factors influencing machining accuracy and workpiece quality, yet effective control methods for these forces across various difficult-to-machine materials remain limited. However, the current research on grinding force prediction models for various difficult-to-machine materials lacks a corresponding review to provide unified guidance. Based on this, this study addresses this gap by analyzing and summarizing cutting and grinding force models for these materials. First, cutting and grinding force models for various difficult-to-machine materials are classified and reviewed. Based on material characteristics and machining performance, difficult-to-machine materials are categorized as super alloys, hard brittle materials, and composite materials, with the error ranges of corresponding force models summarized. Subsequently, the application of these models in machining processes is discussed, identifying the main factors affecting cutting and grinding forces and examining how machining methods influence these forces. Additionally, based on model application, the most widely recognized and applicable force model for various materials is identified. Finally, potential future research directions are proposed to address current challenges in grinding force research. This study aims to provide theoretical guidance and technical support for predicting cutting and grinding forces in difficult-to-machine materials to enhance surface quality.