A comprehensive cutting tool adaptation method for multi-feature part based on evolutionary game algorithm

Abstract

The adaptation of cutting tools is the key link in machining. Although a large amount of work has been done to achieve tool selection for a single feature, there is relatively little research on tool scheme adaptation for multi-feature parts. Considering the factors of matching, efficiency, cost, and environment, a comprehensive optimization method for a multi-feature part tool scheme is proposed in this work. First, the critical tool of a complex feature is defined, and a tool combination method with complex single features is proposed to generate an efficient tool strategy. Then, a tool scheme optimization model for multi-feature parts is constructed in which each machining feature is mapped to a game player in the model space, and the set of available tools is mapped to the player strategies. In addition, the classical evolutionary game algorithm is improved to adapt to the model, according to the difference in the features number and type of different parts. Finally, a square test piece is taken as a case to verify the proposed method. The result shows that the method presented in this work can efficiently obtain the customer-preferred tool scheme for the part.