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Optimized Machining Condition Selection for High-Quality Surface in High-Speed Finish Milling of Molds

Today, the trend in die and mold manufacturing is to pursue high-quality surface topology using high-speed finish milling operation. This paper presents a new approach to optimize machining conditions according to the required material removal rate (MRR), focusing on obtaining a high-quality surface. In this approach, the prediction model of surface roughness using the 2-staged artificial neural network (ANN) is employed for the objective function. Furthermore, an additional surface quality criterion is also used for the optimization problem using the genetic algorithm. It has been investigated that optimized machining conditions can be selected to obtain the high-quality surface within allowable reliability while maintaining a high-quality surface, under the given desired MRR.