Optimization of the economics of machining comprises the determination of the optimal cutting speed and tool replacement policy. A necessary input to the above approach is knowledge of the parameters of the tool life equation which links tool life to cutting speed. In reality, these parameters are not known and should be estimated based on actual machining data. This paper addresses the above optimization problem in the framework of an adaptive control policy. Replacement times in one production run are used to estimate the mean-time-to-failure of a tool, which is in turn used in a regression model to update estimators of the tool life parameters. Using the newly updated estimates a new cutting speed and preventive replacement policy are then determined for the next production run. The end result is an easily implementable decision making tool which can aid in the continuous improvement of the machining process.
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November 1996
Research Papers
Adaptive Tool Replacement Policies in Machining Economics
E. Iakovou,
E. Iakovou
Department of Industrial Engineering, University of Miami, P. O. Box 248294, Coral Gables, FL 33124
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C. M. Ip,
C. M. Ip
Department of Industrial Engineering, University of Miami, P. O. Box 248294, Coral Gables, FL 33124
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C. Koulamas
C. Koulamas
Decision Sciences and Information Systems, Florida International University, Miami, FL 33199
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E. Iakovou
Department of Industrial Engineering, University of Miami, P. O. Box 248294, Coral Gables, FL 33124
C. M. Ip
Department of Industrial Engineering, University of Miami, P. O. Box 248294, Coral Gables, FL 33124
C. Koulamas
Decision Sciences and Information Systems, Florida International University, Miami, FL 33199
J. Manuf. Sci. Eng. Nov 1996, 118(4): 658-663 (6 pages)
Published Online: November 1, 1996
Article history
Received:
February 1, 1994
Revised:
August 1, 1995
Online:
January 17, 2008
Citation
Iakovou, E., Ip, C. M., and Koulamas, C. (November 1, 1996). "Adaptive Tool Replacement Policies in Machining Economics." ASME. J. Manuf. Sci. Eng. November 1996; 118(4): 658–663. https://doi.org/10.1115/1.2831082
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