Optimization of process parameters of mechanical type advanced machining processes using genetic algorithms

Abstract

Generally, unconventional or advanced machining processes (AMPs) are used only when no other traditional machining process can meet the necessary requirements efficiently and economically because use of most of AMPs incurs relatively higher initial investment, maintenance, operating, and tooling costs. Therefore, optimum choice of the process parameters is essential for the economic, efficient, and effective utilization of these processes. Process parameters of AMPs are generally selected either based on the experience, and expertise of the operator or from the propriety machining handbooks. In most of the cases, selected parameters are conservative and far from the optimum. This hinders optimum utilization of the process capabilities. Selecting optimum values of process parameters without optimization requires elaborate experimentation which is costly, time consuming, and tedious. Process parameters optimization of AMPs is essential for exploiting their potentials and capabilities to the fullest extent economically. This paper describes optimization of process parameters of four mechanical type AMPs namely ultrasonic machining (USM), abrasive jet machining (AJM), water jet machining (WJM), and abrasive-water jet machining (AWJM) processes using genetic algorithms giving the details of formulation of optimization models, solution methodology used, and optimization results.