A Conflict Detection Model Based on Constraint Satisfaction in Food Product Collaborative Design

With the market competition increasing, in order to shorten product development cycle and reduce the development costs, product design is changed from the traditional serial-type process to the parallel, collaborative development process. Food product collaborative design of Feature modeling refers to the number of the design team through the division of labor and cooperation has completed a product development project process. The set with known constraints was detected by interval propagation algorithm. Meanwhile, BP neural network was proposed in this study to detect the set with unknown constraints. Simulated results indicated that BP neural network optimized by IA has better performance in convergent speed and global searching ability compared with Genetic Algorithm (GA).The constraints of two sets were detected respectively.