In this paper, a dynamic model for removal of edge burrs with a compliant brushing tool is reported. Description of the burr geometry is assumed to be known through on-line measurement methods such as a computer vision system in the flexible manufacturing cell. Dynamic response of the brush/workpiece system is evaluated on the basis of experimentally obtained data. Master Curves are introduced as machining descriptors which characterize the incremental burr removal performance of the brush/workpiece system, leading to the development of an analytical dynamic model for orthogonal burr removal using a finite-width brushing tool. Based upon the dynamic model for material removal, a control strategy for automatic deburring is presented for burr configurations having constant height as well as variable height. A closed-form solution for transverse brush feed rate is obtained which is applicable for removal of burrs having variable height, as described by suitable geometry functions. For illustrative purposes, simulations are carried out for a straight-edge burr profile and sinusoidal burr geometry. Results are reported which identify important relationships among brush feed rate, brush penetration depth, and brush rotational speed. In order to help assess the validity of the proposed analytical model and control strategy, experimental results are reported for a combination ramp/straight-edge burr configuration. The results demonstrate generally good correlation between the predicted and actual profile for the edge burr that has been machined. In addition, some important observations include; (1) burr removal is most rapidly carried out by using the highest brush speed and deepest brush/workpiece penetration depth, subject to the condition that the brush fiber is not damaged, (2) Currently available polymer abrasive brushing tools exhibit very slow machining characteristics and must be improved in order to be used in a production environment where burr size is appreciable, (3) Material removal characteristics of the leading and trailing edge of brushes may be a source of error which merits further investigation.

1.
Cariapa, V., Stango, R. J., Chen, L., and Hermann, R., “Development of Process Model for Robotic Adaptive Control of Compliant Tool Deburring Operations,” Proceedings of the 7th International Conference on Systems Engineering, Las Vegas, NV, July 18–20, 1990.
2.
Cariapa
V.
,
Stango
R. J.
,
Chen
L.
, and
Hermann
R.
, “
Aspects of Process Model for Automatic Control of Edge-deburring with Filamentary Brush
,”
ASME JOURNAL OF ENGINEERING FOR INDUSTRY
, Vol.
114
, No.
3
, pp.
294
300
,
1992
.
3.
Chen, L., Stango, R. J., and Cariapa, V., “Automated Prototype Deburring with Compliant Brushing Tool,” ASME Symposium on Intelligent Design and Manufacturing for Prototyping, Atlanta, GA, PED Vol. 50, pp. 147–162, 1991.
4.
Chen, L., Stango, R. J., and Cariapa, V., “Development of Force-control Model for Edge Deburring with Filamentary Brush,” ASME IMECE Symposium on Automatic Deburring and Finishing Methods, MED Vol. 6-1, Manufacturing Science and Engineering, Vol. 1, pp. 281–291, Dallas, TX, November 1997.
5.
FitzPatrick, P. R., and Paul, F. W., “Robotics Finishing Using Brushes-Material Removal Mechanics,” SME Proceedings, Deburring and Surface Conditioning ’87, Phoenix, AZ. MR87-156, 1987.
6.
Hollowell, R., and Guile, R., “An Analysis of Robotic Chamfering and Deburring,” Modeling and Control of Robotic Manipulators and Manufacturing Processes, ASME Winter Annual Meeting, Boston, MA, December 13–18, 1987.
7.
Hollowell, R., “Hybrid Force/Position Control for Robotic Light Machining,” Robotics and Remote Systems Conference, Charleston, SC, March 1989.
8.
Kazerooni, H., Bausch, J. J., and Kramer, B. M.,“Automated Deburring by Robot Manipulators,” American Control Conference, pp. 1749–1755, 1986.
9.
Kazerooni, H., “Hybrid Force/Position Control in Robotic Deburring,” Modeling and Control of Robotic Manipulators and Manufacturing Processes, DSC-Vol. 6, ASME, pp. 55–63, 1987.
10.
Little, J. J., Lowe, D. G., Mackworth, A. K., Pai, D. K., and Woodham, R. J., “Constraint-Based Visual Robotic Systems,” Proceedings of the First World Congress on Intelligent Manufacturing, Processes and Systems, Vol. 1, pp. 668–677, February 13–17, 1995.
11.
Murphy, K. N., and Proctor, F. M., “An Advanced Deburring and Chamfering System,” Third International Symposium on Robotics and Manufacturing, British Columbia, Canada, July, 1990.
12.
Pandit, S. M., and Wu, S. M., Time Series and Systems Analysis with Applications, John Wiley and Sons, New York, NY, 1983.
13.
Paul, F. W., and Fitzpatrick, P. R., “Robotic Controlled Brush Finishing,” Robotics: Theory and Applications, Symposium Volume, ASME, pp. 101–107, 1986.
14.
Paul, F. W., and Fitzpatrick, P. R., “Dynamic System Analysis of Robot Assisted Brush Finishing,” Proceedings of the ASME Winter Meeting, 1987.
15.
Proctor, F. M., and Murphy, K. N., “Keynote Address: Advanced Deburring System Technology,” Proceedings of PED, Symposium on the Mechanics of Deburring and Surface Finishing Process, ASME Winter Annual Meeting, San Francisco, CA, December 12–15, 1989.
16.
Stango
R. J.
,
Heinrich
S. M.
, and
Shia
C. Y.
, “
Analysis of Constrained Filament Deformation and Stiffness Properties of Brushes
,”
ASME JOURNAL OF ENGINEERING FOR INDUSTRY
, Vol.
111
, pp.
238
243
, August,
1989
.
17.
Stango
R. J.
,
Cariapa
V.
,
Liang
S. K.
, and
Prasad
A.
, “
Measurement and Analysis of Brushing Tool Performance Characteristics: Part I and Part II
,”
ASME JOURNAL OF ENGINEERING FOR INDUSTRY
, Vol.
133
, No.
3
, pp.
283
296
,
1991
.
18.
Stango
R. J.
,
Fournelle
R. A.
, and
Chada
S.
, “
Morphology of Surfaces Generated by Circular Wire Brushes
,”
ASME JOURNAL OF ENGINEERING FOR INDUSTRY
, Vol.
117
, No.
1
, pp.
9
15
,
1995
.
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