Optimization of Cutting Parameters for Hard Boring of AISI 4340 Steel Using Signal-to-Noise Ratio, Grey Relation Analysis and Analysis of Variance

Abstract

Tool vibration in the boring process is the main concern because of the tool overhanging which leads to high tool wear, cutting force and cutting temperature. Interaction between machine dynamics and the metal cutting operation tool also results in tool vibration. The optimized cutting parameters will able to decrease tool vibration and in turn, increase the productivity in the manufacturing sector. In this study, statistical mathematical approaches to develop models for determining the impact of individual cutting parameters on cutting temperature, tool wear, cutting force, and tool vibration when hard boring AISI 4340 steels. During hard boring of AISI 4340 steel, the current investigation consisted of 27 run trials with three varying levels of cutting velocity, feed rate, and depth of cut and each of these variables was tested at three different levels. This work intends to simultaneous optimize statistical analysis such as Signal-to-Noise (S/N) ratio, Analysis of Variance (ANOVA) and Grey Relational Analysis (GRA). ANOVA and S/N ratio is used to identify the important cutting parameters on the single response optimization and GRA is used to optimize the multi-response optimization technique on cutting parameters. The results shows that both single and multi-response optimization technique shows the same optimized cutting parameter.