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摘要
Due to the complicated dependencies among design tasks, design changes in a design task can cause changes to many other tasks, which may cost a lot of time and resources to completely resolve them. Therefore, optimal scheduling of design change propagations is required to reduce the total process time. This article presents an integrated approach for scheduling design changes in the complex product development process by combining simulation of change propagations with optimization algorithms. The process model is built using And/or graphs, which can take the logic relationships among design tasks into the process model. Genetic algorithm is applied to the change process model to find the optimal propagation likelihood for each optional propagation path in order to obtain the shortest process run time. The approach is incorporated into the process-oriented computer-aided product design system, and two design changes occurring in the motorcycle engine design process, namely an initiated and an emergent design changes, are used to test the approach. The initiated design change case shows the integrated approach can find the optimal solution more efficiently than the Monte Carlo simulation method, while the emergent change case demonstrates the approach can timely find the optimal solution to the change especially when designers are pressed for delivery of their achievements.
