Performance-based predictive models and optimization methods for turning operations and applications: Part 3 - Optimum cutting conditions and selection of cutting tools

X. Wang, Z. J. Da, A. K. Balaji, I. S. Jawahir

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

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 languageEnglish
Pages (from-to)61-74
Number of pages14
JournalJournal of Manufacturing Processes
Volume9
Issue number1
DOIs
StatePublished - 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

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