Development of hybrid predictive models and optimization techniques for machining operations

I. S. Jawahir, X. Wang

Research output: Contribution to journalArticlepeer-review

48 Scopus citations

Abstract

This paper presents a summary of recent developments in modeling and optimization of machining processes, focusing on turning and milling operations. With a brief analysis of past research on predictive modeling, the paper presents the analytical, numerical and empirical modeling efforts for 2D and 3D chip formation covering the development of a universal slip-line model, a comprehensive finite element model, and integrated hybrid models. This includes a newly developed equivalent toolface (ET) model and new tool-life relationships developed for machining with complex grooved tools. At the end, a performance-based machining optimization method developed for predicting optimum cutting conditions and cutting tool selection is presented. The paper also highlights the need for considering a machining systems approach to include the integrated effects of workpiece, cutting tool and machine tool.

Original languageEnglish
Pages (from-to)46-59
Number of pages14
JournalJournal of Materials Processing Technology
Volume185
Issue number1-3
DOIs
StatePublished - Apr 30 2007

Bibliographical note

Funding Information:
The authors of this paper gratefully acknowledge the financial support of the National Science Foundation (NSF) and Kentucky Science and Engineering Foundation (KSEF) for research on predictive model development for machining. Administrative and laboratory support provided by the Center for Manufacturing at the University of Kentucky is also acknowledged.

Keywords

  • Cutting tools
  • Finite element model
  • Machining performance
  • Modeling
  • Optimization
  • Slip-line model

ASJC Scopus subject areas

  • Ceramics and Composites
  • Computer Science Applications
  • Metals and Alloys
  • Industrial and Manufacturing Engineering

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