Models and Optimization Techniques of Machining Parameters in Turning Operations

Abstract

Machining parameters optimization is one of the most essential and interesting problems in manufacturing world. Efficient optimization of machining parameters can produce high-quality products with low cost and high productivity. Thus, many process optimization models of the turning operations with one or two tools are established in order to realize various machining aims. Due to the complexity of optimization models, many new optimization techniques are proposed to solve them. Major optimization techniques include genetic algorithms, simulated annealing, ant colony optimization, particle swarm optimization, et cetera. In this chapter, a comprehensive discussion on various soft computing techniques are presented, especially meta-heuristic algorithms concerning optimization of machining parameters in both single-tool and multi-tools turning operations. In addition, some future challenges and research trends are also discussed in this chapter.