The wear of wiper inserts directly affects the finishing surface quality in multi-insert face milling. This research aims at monitoring the wear of wiper inserts, using 3D surface form as tool wear indicators. 3D surface height map of the face-milled surface is measured by a high definition metrology (HDM) instrument and converted into height-encoded and toolmark-straightened gray images. 3D surface form indicators, including entropy and contrast, are extracted from the converted images with a modified gray level co-occurrence matrix (GLCM) method. Meanwhile, the wear of wiper inserts is measured using a tool presetter and measuring machine without dismounting wiper inserts from the cutter. Experimental results indicate that entropy shows a strong correlation with average axial wear of the wiper edges and contrast reflects the evolution of axial offset between wiper inserts.

References

1.
Roth
,
J. T.
,
Djurdjanovic
,
D.
,
Yang
,
X.
,
Mears
,
L.
, and
Kurfess
,
T.
,
2010
, “
Quality and Inspection of Machining Operations: Tool Condition Monitoring
,”
ASME J. Manuf. Sci. Eng.
,
132
(
4
), p.
041015
.10.1115/1.4002022
2.
Pfeifer
,
T.
, and
Wiegers
,
L.
,
2000
, “
Reliable Tool Wear Monitoring by Optimized Image and Illumination Control in Machine Vision
,”
Measurement
,
28
(
3
), pp.
209
218
.10.1016/S0263-2241(00)00014-2
3.
Jurkovic
,
J.
,
Korosec
,
M.
, and
Kopac
,
J.
,
2005
, “
New Approach in Tool Wear Measuring Technique Using CCD Vision System
,”
Int. J. Mach. Tools Manuf.
,
45
(
9
), pp.
1023
1030
.10.1016/j.ijmachtools.2004.11.030
4.
Kerr
,
D.
,
Pengilley
,
J.
, and
Garwood
,
R.
,
2006
, “
Assessment and Visualisation of Machine Tool Wear Using Computer Vision
,”
Int. J. Adv. Manuf. Technol.
,
28
(
7–8
), pp.
781
791
.10.1007/s00170-004-2420-0
5.
Castejón
,
M.
,
Alegre
,
E.
,
Barreiro
,
J.
, and
Hernández
,
L. K.
,
2007
, “
On-Line Tool Wear Monitoring Using Geometric Descriptors From Digital Images
,”
Int. J. Mach. Tools Manuf.
,
47
(
12–13
), pp.
1847
1853
.10.1016/j.ijmachtools.2007.04.001
6.
Shahabi
,
H. H.
, and
Ratnam
,
M. M.
,
2009
, “
In-Cycle Monitoring of Tool Nose Wear and Surface Roughness of Turned Parts Using Machine Vision
,”
Int. J. Adv. Manuf. Technol.
,
40
(
11–12
), pp.
1148
1157
.10.1007/s00170-008-1430-8
7.
Wang
,
X.
, and
Kwon
,
P. Y.
,
2014
, “
Wc/Co Tool Wear in Dry Turning of Commercially Pure Aluminium
,”
ASME J. Manuf. Sci. Eng.
,
136
(
3
), p.
031006
.10.1115/1.4026514
8.
Oraby
,
S. E.
,
Al-Modhuf
,
A. F.
, and
Hayhurst
,
D. R.
,
2004
, “
A Diagnostic Approach for Turning Tool Based on the Dynamic Force Signals
,”
ASME J. Manuf. Sci. Eng.
,
127
(
3
), pp.
463
475
.10.1115/1.1948397
9.
Kious
,
M.
,
Ouahabi
,
A.
,
Boudraa
,
M.
,
Serra
,
R.
, and
Cheknane
,
A.
,
2010
, “
Detection Process Approach of Tool Wear in High Speed Milling
,”
Measurement
,
43
(
10
), pp.
1439
1446
.10.1016/j.measurement.2010.08.014
10.
Kaya
,
B.
,
Oysu
,
C.
, and
Ertunc
,
H. M.
,
2011
, “
Force-Torque Based On-Line Tool Wear Estimation System for CNC Milling of Inconel 718 Using Neural Networks
,”
Adv. Eng. Software
,
42
(
3
), pp.
76
84
.10.1016/j.advengsoft.2010.12.002
11.
Alonso
,
F. J.
, and
Salgado
,
D. R.
,
2008
, “
Analysis of the Structure of Vibration Signals for Tool Wear Detection
,”
Mech. Syst. Signal Process.
,
22
(
3
), pp.
735
748
.10.1016/j.ymssp.2007.09.012
12.
Kilundu
,
B.
,
Dehombreux
,
P.
, and
Chiementin
,
X.
,
2011
, “
Tool Wear Monitoring by Machine Learning Techniques and Singular Spectrum Analysis
,”
Mech. Syst. Signal Process.
,
25
(
1
), pp.
400
415
.10.1016/j.ymssp.2010.07.014
13.
Jesús
,
R.-T. R. D.
,
Gilberto
,
H.-R.
,
Iván
,
T.-V.
, and
Carlos
,
J.-C. J.
,
2003
, “
Driver Current Analysis for Sensorless Tool Breakage Monitoring of CNC Milling Machines
,”
Int. J. Mach. Tools Manuf.
,
43
(
15
), pp.
1529
1534
.10.1016/j.ijmachtools.2003.08.004
14.
Salgado
,
D. R.
, and
Alonso
,
F. J.
,
2007
, “
An Approach Based on Current and Sound Signals for in-Process Tool Wear Monitoring
,”
Int. J. Mach. Tools Manuf.
,
47
(
14
), pp.
2140
2152
.10.1016/j.ijmachtools.2007.04.013
15.
Marinescu
,
I.
, and
Axinte
,
D. A.
,
2008
, “
A Critical Analysis of Effectiveness of Acoustic Emission Signals to Detect Tool and Workpiece Malfunctions in Milling Operations
,”
Int. J. Mach. Tools Manuf.
,
48
(
10
), pp.
1148
1160
.10.1016/j.ijmachtools.2008.01.011
16.
Yen
,
C.-L.
,
Lu
,
M.-C.
, and
Chen
,
J.-L.
,
2013
, “
Applying the Self-Organization Feature Map (SOM) Algorithm to Ae-Based Tool Wear Monitoring in Micro-Cutting
,”
Mech. Syst. Signal Process.
,
34
(
1–2
), pp.
353
366
.10.1016/j.ymssp.2012.05.001
17.
Attanasio
,
A.
,
Ceretti
,
E.
,
Giardini
,
C.
, and
Cappellini
,
C.
,
2013
, “
Tool Wear in Cutting Operations: Experimental Analysis and Analytical Models
,”
ASME J. Manuf. Sci. Eng.
,
135
(
5
), p.
051012
.10.1115/1.4025010
18.
Dutta
,
S.
,
Datta
,
A.
,
Chakladar
,
N. D.
,
Pal
,
S. K.
,
Mukhopadhyay
,
S.
, and
Sen
,
R.
,
2012
, “
Detection of Tool Condition From the Turned Surface Images Using an Accurate Grey Level Co-Occurrence Technique
,”
Precis. Eng.
,
36
(
3
), pp.
458
466
.10.1016/j.precisioneng.2012.02.004
19.
Kassim
,
A. A.
,
Mannan
,
M. A.
, and
Mian
,
Z.
,
2007
, “
Texture Analysis Methods for Tool Condition Monitoring
,”
Image Vis. Comput.
,
25
(
7
), pp.
1080
1090
.10.1016/j.imavis.2006.05.024
20.
Wilkinson
,
P.
,
Reuben
,
R. L.
,
Jones
,
J. D. C.
,
Barton
,
J. S.
,
Hand
,
D. P.
,
Carolan
,
T. A.
, and
Kidd
,
S. R.
,
1997
, “
Surface Finish Parameters as Diagnostics of Tool Wear in Face Milling
,”
Wear
,
205
(
1–2
), pp.
47
54
.10.1016/S0043-1648(96)07253-5
21.
Dutta
,
S.
,
Pal
,
S. K.
,
Mukhopadhyay
,
S.
, and
Sen
,
R.
,
2013
, “
Application of Digital Image Processing in Tool Condition Monitoring: A Review
,”
CIRP J. Manuf. Sci. Technol.
,
6
(
3
), pp.
212
232
.10.1016/j.cirpj.2013.02.005
22.
ISO, ISO 25178-602:2010
,
2010
,
Geometrical Product Specifications (GPS)—Surface Texture: Areal—Part 602: Nominal Characteristics of Non-Contact (Confocal Chromatic Probe) Instruments
,
ISO
,
Geneva, Switzerland
.
23.
Huang
,
Z.
,
Shih
,
A. J.
, and
Ni
,
J.
,
2006
, “
Laser Interferometry Hologram Registration for Three-Dimensional Precision Measurements
,”
ASME J. Manuf. Sci. Eng.
,
128
(
4
), pp.
1006
1013
.10.1115/1.2335856
24.
Liao
,
Y.
,
Stephenson
,
D. A.
, and
Ni
,
J.
,
2010
, “
A Multifeature Approach to Tool Wear Estimation Using 3D Workpiece Surface Texture Parameters
,”
ASME J. Manuf. Sci. Eng.
,
132
(
6
), p.
061008
.10.1115/1.4002852
25.
Wang
,
M.
,
Xi
,
L.
, and
Du
,
S.
,
2014
, “
3D Surface Form Error Evaluation Using High Definition Metrology
,”
Precis. Eng.
,
38
(
1
), pp.
230
236
.10.1016/j.precisioneng.2013.08.008
26.
de Souza
,
A. M.
, Jr.
,
Sales
,
W. F.
,
Santos
,
S. C.
, and
Machado
,
A. R.
,
2005
, “
Performance of Single Si3N4 and Mixed Si3N4+PCBN Wiper Cutting Tools Applied to High Speed Face Milling of Cast Iron
,”
Int. J. Mach. Tools Manuf.
,
45
(
3
), pp.
335
344
.10.1016/j.ijmachtools.2004.08.006
27.
Astakhov
,
V. P.
,
2004
, “
The Assessment of Cutting Tool Wear
,”
Int. J. Mach. Tools Manuf.
,
44
(
6
), pp.
637
647
.10.1016/j.ijmachtools.2003.11.006
28.
Al-Kindi
,
G.
, and
Zughaer
,
H.
,
2012
, “
An Approach to Improved CNC Machining Using Vision-Based System
,”
Mater. Manuf. Process.
,
27
(
7
), pp.
765
774
.10.1080/10426914.2011.648249
29.
Dutta
,
S.
,
Kanwat
,
A.
,
Pal
,
S. K.
, and
Sen
,
R.
,
2013
, “
Correlation Study of Tool Flank Wear With Machined Surface Texture in End Milling
,”
Measurement
,
46
(
10
), pp.
4249
4260
.10.1016/j.measurement.2013.07.015
30.
Nguyen
,
H. T.
,
Wang
,
H.
, and
Hu
,
S. J.
,
2013
, “
Characterization of Cutting Force Induced Surface Shape Variation in Face Milling Using High-Definition Metrology
,”
ASME J. Manuf. Sci. Eng.
,
135
(
4
), p.
041014
.10.1115/1.4024290
31.
Haralick
,
R. M.
,
Shanmugam
,
K.
, and
Dinstein
,
I. H.
,
1973
, “
Textural Features for Image Classification
,”
IEEE Trans. Syst. Man Cybern.
,
3
(
6
), pp.
610
621
.10.1109/TSMC.1973.4309314
You do not currently have access to this content.