Abstract
In this paper, a study on multi-objective optimization of the cylindrical grinding process is presented. The experimental material used in this study is X12M steel. The two output parameters of the grinding process considered in this study are surface roughness and material removal rate (MRR). The cutting mode parameters including cutting speed, feed rate, and cutting depth have been selected as input parameters of the experimental process. Experimental matrix by Taguchi method has been used to design a matrix with 27 experiments. Analysis of experimental results by Pareto chart has determined the effect of input parameters on output parameters. The Data Envelopment Analysis-based Ranking (DEAR) method has been applied to determine the values of input parameters to simultaneously ensure the two criteria of minimum surface roughness and maximum MRR. Finally, the development direction for further studies has also been recommended in this study.
Highlights
Grinding is a method known for a long time because of its machining ability to ensure high accuracy and surface gloss
The determination of the optimal value of input parameters to simultaneously ensure the minimum surface roughness and the maximum material removal rate (MRR) was conducted by Data Envelopment Analysis-based Ranking (DEAR) method
The results show that the cutting speed and feed rate have a significant effect on the surface roughness, in which the effect of cutting speed on the surface roughness is greater than the effect of feed rate
Summary
Grinding is a method known for a long time because of its machining ability to ensure high accuracy and surface gloss. The studies on the grinding process in general and the external cylindrical grinding process, in particular, to ensure the workpiece surface of the machine with slight surface roughness and large MRR have been performed by many authors. This problem is known as the optimization of the grinding process. For studying the optimization of the external cylindrical grinding process, to ensure the minimum surface roughness, the Taguchi method has been applied to design the experimental matrix, followed by the Signal-to-Noise ratio (S/N) to determine the optimal. The determination of the optimal value of input parameters to simultaneously ensure the minimum surface roughness and the maximum MRR was conducted by DEAR method
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