Intelligent setup planning in manufacturing by fuzzy set theory based approach

In this paper, a fuzzy set theory based intelligent approach for setup planning in manufacturing is introduced. The setup planning problem is decomposed into three sub tasks in the proposed approach: the setup generation, operation sequence and setup sequence. The setups are generated according to the optimal machining direction of each feature, which is determined by fuzzy comprehensive judgment method. Using production rules and fuzzy set theory, the feature precedence relationships matrix (FPR) is formed by considering the main influence factors such as feature geometry, datum relationship, heuristic rides and manufacturing cost. Based on the FRP, the operation sequence and setup sequence problems are mapped onto traveling salesman problem (TSP). The Hopfield neural networks based algorithm is adopted to execute these subtasks. An example is illustrated to demonstrate the proposed approach.