Application of fuzzy and rough sets theory in the optimization of machining parameters for mold milling operations

Abstract

NC milling operation has become one of the main means of mold manufacturing in recent years, and the determination of milling conditions is important to assure the quality and minimize the costs of molds. This paper first constructs an optimization model of machining parameters for mold milling operations, focusing on minimizing the production costs. Then, based on the properties of the machining parameters database, it also proposes an extended model of fuzzy and rough sets theory for incomplete information systems, including incomplete continuous attribute values, and applies the model to rules learning from the machining database. Thus, by rule reasoning, the feasible solution space of optimization model can be easily established. At last, an example is presented to detail the optimization of machining parameters in the case of the cavity milling of an injection plastic mold.Keywords Feasible solution space · Fuzzy similarity relationship · Genetic algorithms · Optimization model of mold milling operations · Rough sets · Rules learning Nomenclature C, C i (i = 1 ∼ n) total cost of mold machining, cost of each feature to be machined in a mold C k (k = 1 ∼ n) cost of machining one feature in a mold C m , C 0 machining cost of a mold in unit time, overhead expenses and labor cost in unit time C t , C tw cost of the cutting tool, cost of tool wear in unit time t 1 , t 2 , t 3 machining time, tool changing time, setup time of mold T tool life (min)