The ultimate aim of the manufacturing is to produce the first part correctly and most economically on the production floor. This paper presents computationally efficient mathematical models to predict milling process state variables, such as chip load, force, torque, and cutting edge engagement at discrete cutter locations. Process states are expressed explicitly as a function of helical cutting edge-part engagement, cutting coefficient, and feed rate. Cutters with arbitrary geometry are modeled parametrically, and the intersection of their helical cutting edges with workpiece features are evaluated either analytically or numerically depending on the geometric complexity. Process variables are computed for each cutting edge-part engagement feature and summed to predict the total force, torque, and power generated at each feed rate interval. The proposed algorithms are experimentally verified in simulating milling of a gear box cover, and integrated to the virtual milling process system, which is capable of predicting cutting forces, torque, power, and vibrations within CAM environment.
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e-mail: dmerdol@mech.ubc.ca
e-mail: altintas@mech.ubc.ca
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October 2008
Research Papers
Virtual Simulation and Optimization of Milling Operations—Part I: Process Simulation
S. Doruk Merdol,
S. Doruk Merdol
Manufacturing Automation Laboratory, Department of Mechanical Engineering,
e-mail: dmerdol@mech.ubc.ca
The University of British Columbia
, 6250 Applied Science Lane, Vancouver, BC, V6T 1Z4, Canada
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Yusuf Altintas
Yusuf Altintas
Manufacturing Automation Laboratory, Department of Mechanical Engineering,
e-mail: altintas@mech.ubc.ca
The University of British Columbia
, 6250 Applied Science Lane, Vancouver, BC, V6T 1Z4, Canada
Search for other works by this author on:
S. Doruk Merdol
Manufacturing Automation Laboratory, Department of Mechanical Engineering,
The University of British Columbia
, 6250 Applied Science Lane, Vancouver, BC, V6T 1Z4, Canadae-mail: dmerdol@mech.ubc.ca
Yusuf Altintas
Manufacturing Automation Laboratory, Department of Mechanical Engineering,
The University of British Columbia
, 6250 Applied Science Lane, Vancouver, BC, V6T 1Z4, Canadae-mail: altintas@mech.ubc.ca
J. Manuf. Sci. Eng. Oct 2008, 130(5): 051004 (12 pages)
Published Online: August 14, 2008
Article history
Received:
June 27, 2006
Revised:
March 18, 2007
Published:
August 14, 2008
Citation
Merdol, S. D., and Altintas, Y. (August 14, 2008). "Virtual Simulation and Optimization of Milling Operations—Part I: Process Simulation." ASME. J. Manuf. Sci. Eng. October 2008; 130(5): 051004. https://doi.org/10.1115/1.2927434
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