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.

1.
Ermer
D. S.
, “
A Bayesian Model of Machining Economics for Optimization by Adaptive Control
,”
ASME JOURNAL OF ENGINEERING FOR INDUSTRY
, Vol.
95
, pp.
628
632
,
1970
.
2.
Fenton
R. G.
, and
Joseph
N. D.
, “
The Effects of the Statistical Nature of Tool Life on the Economics of Machining
,”
International Journal of Machine Tool Design Research
, Vol.
19
, pp.
43
50
,
1979
.
3.
Koulamas
C.
, “
Simultaneous Determination of Optimal Machining Conditions and Tool Replacement Policies in Constrained Machining Economics Problems by Geometric Programming
,”
International Journal of Production Research
, Vol.
29
, pp.
2407
2421
,
1991
.
4.
Koulamas
C.
, “
A Note on Incorporating Tool Life Variability in the Geometric Programing Formulation of Machining Economics Problems
,”
HE Transactions
, Vol.
26
, pp.
87
90
,
1994
.
5.
La Commare
U.
,
Noto La Diega
S.
, and
Passannanti
A.
, “
Optimal Tool Replacement Policies With Penalty Cost for Unforeseen Tool Failure
,”
International Journal of Machine Tool Design Research
, Vol.
23
, pp.
237
243
,
1983
.
6.
Nelson, W., Applied Life Data Analysis, John Wiley, 1982.
7.
Neuts, F. M., Matrix-Geometric Solutions in Stochastic Models—An Algorithmic Approach, The John Hopkins University Press, Baltimore, 1981.
8.
Ramalingam
S.
, and
Watson
J. D.
, “
Tool Life Distributions Part 1: Single-Injury Tool Life Model
,”
ASME JOURNAL OF ENGINEERING FOR INDUSTRY
, Vol.
99
, pp.
519
522
,
1977
.
9.
Ramalingam
S.
, “
Tool Life Distributions Part 2: Multiple-Injury Tool Life Model
,”
ASME JOURNAL OF ENGINEERING FOR INDUSTRY
, Vol.
99
, pp.
523
528
,
1977
.
10.
Sheikh
A. K.
,
Kendall
L. A.
, and
Pandit
S. M.
, “
Probabilistic Optimization of Multitool Machining Operations
,”
ASME JOURNAL OF ENGINEERING FOR INDUSTRY
, Vol.
102
, pp.
239
246
,
1980
.
11.
Taylor
F. W.
, “
On the Art of Cutting Metals
,”
Transactions of the ASME
, Vol.
28
, pp.
31
279
,
1907
.
12.
Tijms, H. C., Stochastic Modelling and Analysis: A Computational Approach, John Wiley, 1986.
13.
Wager
J. G.
, and
Barash
M. M.
, “
Study of the Distribution of the Life of HSS Tools
,”
ASME JOURNAL OF ENGINEERING FOR INDUSTRY
, Vol.
93
, pp.
1044
1050
,
1971
.
This content is only available via PDF.
You do not currently have access to this content.