Research Of Product Coupled Functions Planning Based On Immune Computation

Following the flying development of market economy, reducing product cost, improving product quality and shortening product design cycle became keys to economic development, to intelligentize product design which is pivotal act in product design became the inevitable choice for modern enterprise. Otherwise, establishing precise axiomatic system in design field, which is similar to natural science, is significative in modern design. Axiomatic design theory is hot in design field and will be one kind of significant design methods. But at present, the axiomatic design theory still can not be used in complicated product effectively, so, it is necessary to branch axiomatic design out and adopt effective intelligent method to solve problems in coulped design. Artificial immune system, which takes inspirations from biological immune system, is a novel and powerful intelligent computation system. Then, a new product coupled functions planning method based on immune computation is investigated. Namely, the coupled design problems in product design are researched based on axiomatic design theory, and the pivotal technologies about immune computation are used to solve these problems.In the product coupled functions planning method, the functional coupling relation is clustered and recognised using immune algorithm ICRA, which can provide guidance for decoupling and avoid unnecessary loss of coupling information; the functional coupling degree is measured using 1 to 1 compare based on triangle fuzzy numbers, which takes thinking of human being into account; after necessary decoupling, the coupled functions are teared using immune algorithm ITA, in which the best sequence about the coupled functions can be obtained. On the other hand, a software CFPS is designed to realize the coupled functions planning method.Finally, two product cases, viz. horizontal shell & tube condenser and CNC gear measurement center, are solved by the coupled functions planning method when encountering coupled problems in design. Consequently, they prove that this method is effective in solving coupled design problems. In addition, in the case of condenser, certain parameters in ICRA are discussed, and ICRA is compared with genetic algorithm and clustering method based on gragh theory. Accordingly, certain merits about immune computation are represented.