Authors : K.K. Prasad and D. Chaudhary
Abstract: The machining is about outward appearance, the fundamental of contemporary manufacturing industry and is concerned either directly or indirectly in the manufacture of almost every product of recent development. A term that covers a hefty anthology of manufacturing processes designed to remove unwanted material, habitually in the appearance of chips from a work piece to provide desired geometry, size and finish specified to fulfil design requirements. This paves the research intention towards incorporating soft computing techniques to acquire better result in short intervals. This study includes the significance of predicting optimal tuning input parameters such as cutting speed, feed rate, depth of cut and nose radius for minimized surface roughness, maximized material removal rate and minimized tool wear. This objective is achieved by developing a mathematical model which incorporates optimization techniques. Genetic Algorithm (GA) is the ultimate tool to utilize in this research for its bettermen, Genetic algorithm has further developed as Adaptive Genetic Algorithm (AGA) and Opposition based Genetic Algorithm (OGA) amid opposition based Genetic algorithm reveal better performance both in the mathematical model designing and tuning input parameter optimization. In this research three different super alloys have been subjected to turning on CNC lathes with a combination of uncoated and coated carbide turning inserts.
K.K. Prasad and D. Chaudhary, 2018. Effective Utilization of Opposition Based Genetic Algorithm for Multi Objective Optimization of CNC Turning Process. International Journal of Soft Computing, 13: 81-91.