Techniques Used for Optimization of Process Parameters in Milling Operations: Literature Review

Machining is the essential activity of a manufacturing organization and milling is one of them. The economy growth rate of a country depends upon the innovation and research in manufacturing sectors. In this paper an attempt has been made to identify the gap in optimization of process parameters in milling operations through extensive literature review. Literature review revealed that researcher were mainly focus on input process parameter such as cutting speed, feed rate and depth of cut and output process parameters such as material removal rate (MRR), surface finish. The Taughi method and response surface method (RSM) were frequently used to optimize the process parameter. It was found that very less work support the process parameter optimization in which different weightage has been assigned to output parameters as per application of machining process. The little work reported in which algorithm and application of multiple criteria decision making approaches such as particle swarm optimization (PSO), teaching learning based optimization (TLBO), Genetic algorithm (GA) was implemented to optimize the parameters. The guidelines were provided for further research in optimization of process parameters.