Prediction and optimization of process parameters in chemical mechanical polishing for 304 stainless steel based on response surface methodology

LIU Haixu; WU Qingdong; CAO Xiaojun; QI Wanting; SU Jianxiu

doi:10.13394/j.cnki.jgszz.2021.2.0015

Volume 41 Issue 2

Apr. 2021

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Article Navigation > Diamond & Abrasives Engineering > 2021 > 41(2): 89-95

LIU Haixu, WU Qingdong, CAO Xiaojun, QI Wanting, SU Jianxiu. Prediction and optimization of process parameters in chemical mechanical polishing for 304 stainless steel based on response surface methodology[J]. Diamond & Abrasives Engineering, 2021, 41(2): 89-95. doi: 10.13394/j.cnki.jgszz.2021.2.0015

Citation:

LIU Haixu, WU Qingdong, CAO Xiaojun, QI Wanting, SU Jianxiu. Prediction and optimization of process parameters in chemical mechanical polishing for 304 stainless steel based on response surface methodology[J]. Diamond & Abrasives Engineering, 2021, 41(2): 89-95. doi: 10.13394/j.cnki.jgszz.2021.2.0015

Citation:

LIU Haixu, WU Qingdong, CAO Xiaojun, QI Wanting, SU Jianxiu. Prediction and optimization of process parameters in chemical mechanical polishing for 304 stainless steel based on response surface methodology[J]. Diamond & Abrasives Engineering, 2021, 41(2): 89-95. doi: 10.13394/j.cnki.jgszz.2021.2.0015

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Prediction and optimization of process parameters in chemical mechanical polishing for 304 stainless steel based on response surface methodology

doi: 10.13394/j.cnki.jgszz.2021.2.0015

School of Mechanical and Electrical Engineering, Henan Institute of Science and Technology, Xinxiang 453003, Henan, China

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Rev Recd Date: 2020-12-02

Available Online: 2022-04-06

Abstract

Abstract

Response surface methodology was used to study the effects of three parameters (rotating speed, pressure and time) on material removal rate R_MRR and surface roughness R_a in polishing process. According to the results of polishing test, the regression model of material removal rate and surface roughness was established, the response surface and contour map were obtained, and analyzed in detail. The results show that the regression model is significant, which proves the feasibility and reliability of the response surface method to predict and optimize the process parameters of 304 stainless steel chemical mechanical polishing. The optimum process parameters of surface roughness and material removal rate were obtained. The experimental values of R_a and R_MRR were compared with the predicted values, and the relative error was within ±10%. The results show that the precision of the model is high, and it can be used to optimize the process parameters and predict the results.
- response surface methodology,
- 304 stainless steel,
- chemical mechanical polishing,
- process parameter,
- material removal rate

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