TOWARDS PREDICTIVE MODELING AND OPTIMIZATION OF MACHINING OPERATIONS

I. S. Jawahir, A. K. Balaji, R. Stevenson, C. A. van Luttervelt

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

16 Scopus citations

Abstract

The objective of this paper is to introduce an applied systems approach for prediction and optimization of machining performance. Current techniques for assessing machining performance are highly localized and traditionally biased towards the work material. An integrated systems approach i.s proposed for a reliable and consistent assessment of applied machining performance (AMP). Three areas, namely: fundamental modeling, applied modeling and optimization. are fix;used on. Fundamental mixieling entails generic predictive inotlcls for machining performance measures (cutting forces/ torque/power, tool-wear/tiKil-life, chip form/chip breakability, surface roughness/surface integrity, part accuracy, etc.). Applied modeling involves application of the generic mcxlels to a specific machining system, including the interactions of the three major elements: workpiece, machine ttK,l and cutting tool. The subsequent step of optimization predicts the optimized machining performance (OMP).

Original languageEnglish
Title of host publicationManufacturing Science and Engineering
Subtitle of host publicationVolume 2
Pages3-12
Number of pages10
ISBN (Electronic)9780791826799
DOIs
StatePublished - 1997
EventASME 1997 International Mechanical Engineering Congress and Exposition, IMECE 1997 - Manufacturing Science and Engineering - Dallas, United States
Duration: Nov 16 1997Nov 21 1997

Publication series

NameASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
Volume1997-W

Conference

ConferenceASME 1997 International Mechanical Engineering Congress and Exposition, IMECE 1997 - Manufacturing Science and Engineering
Country/TerritoryUnited States
CityDallas
Period11/16/9711/21/97

Bibliographical note

Funding Information:
New research findings presented in this paper are largely from the various sponsored projects at the University of Kentucky. The authors gratefully acknowledge the generou.s funding of these projects by the National Science Foundation, General Motors Corporation, Ford Motor Company, Kennametal Inc. and the Center for Robotics and Manufacturing Systems at the University of Kentucky. The authors extend their sincere appreciation to Prof. E. J. A. Annarego (University of Melbourne, Australia) and Prof. V. A. Astakhov (Concordia University, Canada) for their constructive comments and encouragement during the preparation of this paper.

Publisher Copyright:
© 1997 American Society of Mechanical Engineers (ASME). All rights reserved.

ASJC Scopus subject areas

  • Mechanical Engineering

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