Optimization of Non-Traditional Machining Processes: A Review

Abstract

Conventional machining processes are substituted by non-traditional (NTM) machining processes due to rising demands in high surface finishing and complex type geometries. To achieve the needed precision and burr-free machined surface, these NTM processes use energy in its direct form to remove materials in the form of atoms or molecules. In order to utilize the optimal abilities of the NTM processes, determining the optimal combinations of their controllable parameters has often been required. Various non-conventional optimization techniques have been used to address the process optimization problems due to their inherent benefits and capabilities in finding nearly global optimal solutions. This paper examines the implementations of different non-conventional optimization techniques for parametric optimization of NTM processes. It is recognized that machining processes for the electric discharge were refined several times and procedures for electric discharge were accompanied by wiring machining. In most instances, previous researchers opted to optimize the removal rate of the material. The genetic algorithm was found to be the most influential non-conventional optimization technique. The paper highlights the optimization of some NTM processes with respect to optimum parameters combinations. The goal is to assist the process engineer in dismissing those NTM processes that are not appropriate for work material limitation, machining process definition, and process characteristic requirements and to slowly narrow down the list of feasible processes in order to arrive at the best possible decision. The conventional machining process cannot be applied to materials with low machinability and complicated geometry growth. The reasons given above compel the industries to adopt unconventional machining processes. In this paper, several research papers presented on parametric optimization of unconventional machining processes are closely analyzed to get an understanding of the chosen process parameters, examined results, machined work materials and methods of optimization used in those processes when generating differing geometries for their industrial usage.