Performance-Based Predictive Models and Optimization Methods for Turning Operations and Applications: Part 3—Optimum Cutting Conditions and Selection of Cutting Tools

This paper presents a summary of recent developments in developing performance-based machining optimization methodologies for turning operations. Four major machining performance measures (cutting force, tool wear/tool life, chip form/chip breakability, and surface roughness) are considered in the present work, which involves the development and integration of hybrid models for single and multi-pass turning operations with and without the effects of progressive tool wear. Nonlinear programming techniques were used for single-pass operations, while a genetic algorithms approach was adopted for multi-pass operations. This methodology offers the selection of optimum cutting conditions and cutting tools for turning with complex grooved tools.