Cutting parameter optimization in milling operations by various solution methods

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.