Milling parameter optimization through a discrete variable transformation

TIEN-CHIEN CHANG College of Engineering, Department of Industrial Engineering and Operations Research, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, 24061, U.S.A

RICHARD A. WYSK College of Engineering, Department of Industrial Engineering and Operations Research, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, 24061, U.S.A

ROBERT P. DAVIS College of Engineering, Department of Industrial Engineering and Operations Research, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, 24061, U.S.A

BYOUNG CHOI College of Engineering, Department of Industrial Engineering and Operations Research, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, 24061, U.S.A

Abstract

Although milling is one of the most common chip metal removal processes, little has been done to aid in identifying the optimum operational conditions for milling processes. In this paper, a mathematical model for milling operations is developed and the five primary control variables identified. The model is then decomposed and an efficient optimization procedure developed for control variable identification.

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Milling parameter optimization through a discrete variable transformation

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Milling parameter optimization through a discrete variable transformation

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