A two-step strategy was proposed to solve the problems that inefficiency and inaccuracy of function modules clustering for complex product. Firstly, the three principles were proposed that weldment simplification, outsourcing simplification and borrowed component reduction to preprocess and simplify complex product. Then the complex product preprocessed can be clustered into different function modules by using the advanced Immune Algorithm amalgamated with heuristic rule (R-Immunity). By comparing the efficiency, accuracy and robustness of function modules clustering among the Genetic Algorithm, the Immune Algorithm and the R-Immunity Algorithm, we consider that the R-Immunity Algorithm is more efficient and precise to solve the problems related to function modules clustering. Finally, starting with the structure properties of complex product, the clustering results were optimized for the purposes of reducing coupling between modules and satisfying configuration requirements of customer.
Explaining how to set up configuration model from the Angle of product family, for the composition of product configuration model of product family structure was analyzed, put forward the definition of product family configuration unit, and used it as the basic elements of product family configuration model. Using various granularity of product family configuration units set to do the unified expression for function, the principle and structure of all products contained in the product family. And did further analyze for the characteristic, types, and associated constraints of product family configuration units. Finally, described the modeling process of product family configuration model. Do verification by the dumper.
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