Multidisciplinary Decision Making Methods in an Information Driven Product Development Framework
New paradigms and accompanying software systems are necessary to support the integration of system level design and discipline level analysis activities for the implementation of product lifecycle management. An information driven product development framework has been developed to integrate these activities using product information model to represents the associativities among design requirements, product models and design parameters. In this paper, product information model is used to not only integrate all the activities and software packages, but also enable formulating and solving design problems using appropriate solution methods. Two engineering examples are solved using three different methods, Genetic Algorithm, Game Based Decision Making method, and Collaborative Decision Making method. The three methods are compared by the numbers of calls to discipline level analysis models. It was shown that collaborative decision making method is capable of finding satisfying solutions with the least number of calls to the computing expensive analysis models.