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Parameter optimization in metal cutting processes plays a key role in satisfying quality requirements of machined parts at low cost. This paper addresses multi-pass face-milling operations. A variety of solution methods including integer programming, nonlinear programming, and genetic algorithms are applied for solving a mathematical model which is based on minimum unit production cost to seek optimal values of cutting speed, feed rate, depth of cut, and the number of passes. Through a case study, it has been shown that our methods are effective and generate lower production cost compared with the methods from the literature.
Machine Learning and Cybernetics (ICMLC), 2011 International Conference on (Volume:1 )
Date of Conference: 10-13 July 2011