Optimizing Process Parameters for Surface Grinding of Heated-Treated Steel: A Combination Approach Utilizing Response Surface Methodology and Taguchi Method

This paper aims to optimize the grinding parameters of a surface grinding machine through the combined application of Response Surface Methodology (RSM) and Taguchi Design. The research investigates the impact of input factors, including the depth of cut in coarse grinding, depth of cut in fine grinding, and number of spark-out, on the quality of heat-treated steel specimens. The selected objective for this study is surface roughness (Ra) minimization. To streamline the experiment process and minimize time requirements, the Taguchi approach was adopted, utilizing an L9 orthogonal array in conjunction with the application of a signal-to-noise (S/N) ratio. The obtained experimental data is further analyzed using statistical techniques and Response Surface Methodology (RSM) to formulate a generalized model equation for this research. The experimental results conclusively demonstrate that the proposed approach can optimize the grinding parameters of the surface grinder, leading to enhanced quality and efficiency of the grinding process with low cost and fewer experiments. The research can be an effective and practical reference for potential research directions and future applications.