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Grinding temperature prediction model of high-volume fraction SiCp/Al composite

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Abstract

Grinding is the main processing technique for particle-reinforced composites, in which grinding force and temperature are significant for investigating the removal mechanism and surface properties. In this study, a grinding force prediction model is established based on the response surface methodology. The energy density of surface heat source in the grinding area is calculated by combining the contact area between the grinding wheel and workpiece. Based on the integration algorithm in time and space, a theoretical ideal grinding temperature prediction model is deduced. The grinding heat energy transfer coefficient is defined as the percentage of heat energy, which is transferred from the grinding heat energy to the workpiece. According to the experimental and ideal theoretical highest grinding temperatures, a prediction model of the heat energy transfer coefficient is established, and the modified theoretical highest grinding temperature prediction model is obtained. Furthermore, a finite element model of SiCp/Al composite in grinding is established. The highest grinding temperature in the finite element model is consistent with the modified theoretical highest grinding temperature, and the grinding temperature field is analysed. The highest grinding temperature increases as the wheel speed and grinding depth increase, while it decreases as table speed increases, which differs from that of some common materials. Thus, the grinding temperature prediction model provides an important reference for the study of removal mechanism and surface properties of SiCp/Al composite.

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Funding

This work was supported by Science and Technology Program of Shanghai, China (Grant No. 20ZR1462800) and the National Natural Science Foundation of China (Grant No. 51875413).

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Authors and Affiliations

  1. School of Mechanical Engineering, Tongji University, Shanghai, 201804, China

    Chuanmin Zhu, Peng Gu, Yinyue Wu & Zhan Tao

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  1. Chuanmin Zhu
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  2. Peng Gu
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  3. Yinyue Wu
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  4. Zhan Tao
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Correspondence to Peng Gu.

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Zhu, C., Gu, P., Wu, Y. et al. Grinding temperature prediction model of high-volume fraction SiCp/Al composite. Int J Adv Manuf Technol 111, 1201–1220 (2020). https://doi.org/10.1007/s00170-020-06098-9

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  • DOI: https://doi.org/10.1007/s00170-020-06098-9

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