Using Wear Curves to Predict the Cost of Changes in Cutting Conditions-Reference-Cited by-同舟云学术

Using Wear Curves to Predict the Cost of Changes in Cutting Conditions

Published:1998-02-01 Issue:1 Volume:120 Page:166-168
ISSN:1087-1357
Container-title:Journal of Manufacturing Science and Engineering
language:en
Short-container-title:

Author:

Chick S.¹,Mendel M. B.²

Affiliation:

1. Dept. of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI 48109

2. Dept. of Industrial Engineering and Operations Research, University of California, Berkeley, CA 94720

Abstract

A recently-proposed probability model for cutting tool lifetimes based on tool wear curves is presented. Optimal tool replacement strategies and cutting conditions are calculated using this wear-based model. The model’s use of wear curves permits extrapolation of cost calculations to cutting conditions for which little statistical data has been collected, assuming data is available for other cutting conditions which have the same failure mechanism. This is particularly important during process design changes, when data is expensive to obtain or limited in quantity. Analysis indicates that an important factor in tool replacement is run-in wear.

Publisher

ASME International

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Control and Systems Engineering

Link

http://asmedigitalcollection.asme.org/manufacturingscience/article-pdf/120/1/166/5931822/166_1.pdf

Reference14 articles.

1. Balazinski M. , and EnnajimiE., 1994, “Influence of Feed Variation on Tool Wear When Milling Stainless Steel 17-4Ph,” ASME JOURNAL OF ENGINEERING FOR INDUSTRY, Vol. 116, pp. 516–520.

2. Barlow, R. E., and Proschan, F., 1981, Statistical Theory of Reliability and Life Testing, To Begin With, Silver Spring, MD.

3. Bayer, R. G., 1994, Mechanical Wear Prediction and Prevention, Marcel Dekker, Inc., New York.

4. Chick, S. E., 1995, “Product and Process Design With Engineering-Based Statistical Models,” PhD thesis, UC Berkeley, Berkeley, CA, Dept. of Industrial Engineering and Operations Research.

5. Chick S. E. , and MendelM. B., 1996, “An Engineering Basis for Statistical Lifetime Models With an Application to Tribology,” IEEE Transactions on Reliability, Vol. 45, No. 2, pp. 208–215.

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