Predictive modeling of machining performance in turning operations

I. S. Jawahir, O. W. Dillon, A. K. Balaji, M. Redetzky, N. Fang

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


Recent definitions of machining performance have been based on technological machining performance measures such as cutting forces, tool-life/tool-wear, chip-form/chip breakability, surface roughness, etc. However, modeling work on these performance measures has so far been characterized by isolated treatment of each of these measures. The modeling approach followed by the machining research group at the University of Kentucky aims for an integrated predictive modeling methodology for the major technological machining performance measures. Extensive use of analytical, experimental, numerical, and AI-based approaches is made in the development of these predictive models. This paper presents the outline of this modeling effort and reports the progress made to date in implementing it.

Original languageEnglish
Pages (from-to)253-276
Number of pages24
JournalMachining Science and Technology
Issue number2
StatePublished - 1998

ASJC Scopus subject areas

  • Materials Science (all)
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering


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