Abstract
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.
Original language | English |
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Pages (from-to) | 61-74 |
Number of pages | 14 |
Journal | Journal of Manufacturing Processes |
Volume | 9 |
Issue number | 1 |
DOIs | |
State | Published - 2007 |
Keywords
- Genetic algorithms
- Multi-pass turning operations
- Optimization methods
- Performance-based predictive modeling
ASJC Scopus subject areas
- Strategy and Management
- Management Science and Operations Research
- Industrial and Manufacturing Engineering