In the authors’ previous work, univariate models were fit to acceleration data to predict impending tool failure. Numerous end-milling life tests, conducted under a wide variety of cutting conditions, demonstrated that the method could consistently warn of impending failure between 6 inches (15 cm) and 8 inches (20 cm) prior to the actual event. This paper presents an improved method that increases the warning time and allows the technique to function independent of the cutting direction or sensor orientation. Using multivariate autoregressive models fit to tri-axial accelerometer signals, monitoring indices are developed, verified and the results are compared with those from the univariate models. The multivariate models detected impending failure 30 inches (76 cm) prior to its occurrence, 23.5 inches (60 cm) earlier than with the univariate models. Furthermore, the multivariate models are able to monitor the condition of the tool, regardless of the cutting direction or sensor orientation. [S1087-1357(00)01003-0]

Issue Section:
Technical Papers
Keywords:
cutting, monitoring, machining, manufacturing processes, quality control, modelling
Topics:
Cutting, Milling, Signals, Failure, Accelerometers, Sensors, Eigenvalues
1.
Pandit
,
S. M.
, and
Kashou
,
S.
,
1982
, “
A Data Dependent Systems Strategy of On-line Tool Wear Sensing
,”
ASME J. Eng. Ind.
,
104
, pp.
217
–
223
.
2.
Tansel
,
I. N.
, and
McLaughlin
,
C.
,
1993
, “
Detection of Tool Breakage in Milling Operations—I. The Time Series Analysis Approach
,”
Int. J. Mach. Tools Manuf.
,
33
, No.
4
, pp.
531
–
544
.
3.
Ruiz, G. H., Mori, K., and Kasashima, N., 1995, “Detection of Tool Failure in Milling Process Using Wavelet Transform,” First World Congress on Int. Manuf. Proc. and Sys., 1, San Juan, Puerto Rico, pp. 271–281.
4.
O’Brien
,
D. J.
,
Sutherland
,
J. W.
, and
Kapoor
,
S. G.
,
1990
, “
A Force-Based Approach to On-Line Flute Breakage Detection in a Peripheral End Milling Process
,”
Autom. Manuf. Proc.
, ASME Bound Volume—DSC
22
,
47
–
58
.
5.
Liu, T., and Lee, C., 1998, “On-Line Evaluation of Drill Conditions for Operational Safety and Product Quality,” MED-Vol. 8, Proceedings of the ASME, pp. 877–884.
6.
Kim
,
S.
, and
Klamecki
,
B. E.
,
1997
, “
Milling Cutter Wear Monitoring Using Spindle Shaft Vibration
,”
ASME J. Manuf. Sci. Eng.
,
119
, pp.
118
–
119
.
1.
Roth
,
J. T.
, and
Pandit
,
S. M.
,
1998
, “
Monitoring End-Mill Wear and Predicting Tool Failure using Accelerometers
,”
J. Manuf. Sci. Eng.
, MED
8
, pp.
867
–
875
.
2.
Also in ASME J. Manuf. Sci. Eng. 121, August 1999.
1.
Lin
,
S. C.
, and
Lin
,
R. J.
,
1996
, “
Tool wear monitoring in face milling using force signals
,”
Wear
,
198
, pp.
136
–
142
.
2.
Wilcox
,
S. J.
, and
Reuben
,
R. L.
,
1994
, “
The detection of short time-scale tool degradation events during face milling operations using cutting force and acoustic emission
,”
J. Eng. Manuf.
,
208
, pp.
205
–
215
.
3.
Altintas
,
Y.
, and
Yellowley
,
I.
,
1989
, “
In-Process Detection of Tool Failure in Milling Using Cutting Force Models
,”
ASME J. Eng. Ind.
,
111
, pp.
149
–
157
.
4.
Diei
,
E. N.
, and
Dornfeld
,
D. A.
,
1987
, “
Acoustic Emission Sensing of Tool Wear in Face Milling
,”
ASME J. Eng. Ind.
,
109
, pp.
234
–
240
.
5.
Sutherland
,
J. W.
,
O’Brien
,
D. J.
, and
Wagner
,
M. S.
,
1989
, “
An Algorithm for the Detection of Flute Breakage in a Peripheral End Milling Process
,”
Trans. NAMRI/SME
,
17
, pp.
144
–
151
.
6.
Altintas
,
Y.
,
Yellowley
,
I.
, and
Tlusty
,
J.
,
1988
, “
The Detection of Tool Breakage in Milling Operations
,”
ASME J. Eng. Ind.
,
110
, pp.
271
–
277
.
7.
Yao
,
Y.
, and
Fang
,
X.
,
1992
, “
Modeling of Multivariate Time Series for Tool Wear Estimation in Finish-Turning
,”
Int. J. Mach. Tools Manuf.
,
32
, No.
4
, pp.
495
–
508
.
8.
Pandit, S. M., 1991, Modal and Spectrum Analysis: Data Dependent Systems in State Space, Wiley, New York.
9.
Pandit, S. M., and Wu, S. M., 1993, Time Series and Systems Analysis with Applications, Wiley, 1983, reprint by Krieger.
10.
Roth, J. T., 1998, Monitoring End-Mill Wear and Predicting Tool Failure using Accelerometers, Ph.D. Thesis, Michigan Technological University.
11.
Roth
,
J. T.
, and
Pandit
,
S. M.
,
1999
, “
Early Prediction of Impending End-Milling Tool Failure Using Acceleration Signals
,”
Tech. Pap. NAMRI/SME
,
27
, pp.
63
–
68
.
12.
Wylie, C. R., and Barrett, L. C., 1982, Advanced Engineering Mathematics, 5th ed., McGraw-Hill, Inc., New York.
13.
Lancaster, P., and Tismenetsky, M., 1985, The Theory of Matrices Second Edition with Applications, 2nd ed., Academic Press, San Diego.
Copyright © 2000
 by ASME
You do not currently have access to this content.