Multi-objective Optimization of Cutting Parameters in Multi-pass Turning Using Genetic Algorithm and Pattern Search

摘要

Optimization of cutting parameters is very important issues in modern manufacturing engineering. This paper proposes a new technique based on the combination of real-coded genetic algorithm (RGA) and pattern search for solving multi-pass turning optimization problems. The machining parameters are determined by multi-objective optimization of maximum production rate and minimum production cost criterion, subject to various practical machining constraints. Experimental results show that the proposed procedure is both effective and efficient, and can be integrated into an intelligent manufacturing system for solving complex machining optimization problems.