On-Line Production Cost Optimization in High Performance Machining Operations through AI Techniques

This paper proposes an on-line adaptive control with optimization (ACO) system for optimizing the production cost subjected to quality constraints in high performance machining operations of hardened steel. Unlike traditional approaches for optimizing production cost, this paper deals with optimizing the cutting operation considering the real state of the cutting-tool. Artificial intelligence techniques for modeling (Artificial Neural Networks) and optimizing (Genetic Algorithms and Mesh Adaptive Direct Search algorithms) are applied for this purpose.