Grey-Based Taguchi Analysis Approach for Optimization of Multi-Objective Problem

Due to the increase in complexity and expectations of more reliable solutions for a problem, the importance of multi-objective problem solutions is increasing day by day. It can play a significant role in making a decision. In the present approach, many combinations of the optimization techniques are proposed by the researchers. These hybrid evolutionary methods integrate positive characteristics of different methods and show the advantage to reach global optimization. In this chapter, Taguchi method and the GRA (Grey Relation Analysis) technique are pronounced and used to optimize a multi-objective metal cutting process to yield maximum performance of tungsten carbide-cobalt cutting tool inserts in turning. L18 orthogonal array is selected to analyze the effect of cutting speed, feed rate, and depth of cut using cryogenically treated and untreated inserts. The performance is evaluated in terms of main cutting force, power consumption, tool wear, and material removal rate using main effect plots of S/N (Signal to Noise) ratios. This chapter indicates that the grey-based Taguchi technique is not only a novel, efficient, and reliable method of optimization, but also contributes to satisfactory solution for multi-machining objectives in the turning process. It is concluded that cryogenically treated cutting tool inserts perform better. However, the feed rate affects the process performance most significantly. Nirmal S Kalsi Beant College of Engineering and Technology Gurdaspur, India Rakesh Sehgal National Institute of Technology Hamirpur, India Vishal S. Sharma Dr. B. R. Ambedkar National Institute of Technology Jalandhar, India

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