Multi-objective optimization for production and quality enhancement in milling of Al 7075 using grey relational analysis

Abstract

Production improvement is a key to stay in the competitive market for most industries. In most of the scenarios, quality gets compensated while going for productivity improvement. Using proper optimization techniques with multi-objective solution tools we might be able to achieve it. Aluminum 7075 material having wide application in lightweight fields such as aviation especially because of its workability nature is taken for experimentation. Milling is one of the significant machining operations in such applications. Here we have attempted to optimize the milling of Al 7075 with two objectives like improving Material Removal Rate and minimizing Surface Roughness. Experimental machining is designed using Taguchi’s design of experiments. The machined data are used to create and analyze the machining operation using the statistical method of calculations. The multi-objective optimization is carried out by Grey relational Analysis and the investigation results are further discussed.