Optimal platform design with modularity strategy under fuzzy environment

Platform has been known as an effective strategy for trading off between product customization and economies of scale, and firms have paid more and more attention to designing an effective and efficient product platform. In platform designing, modularity strategy is usually adopted and new modules are introduced to maintain the variety of products and flexibility of the platform. However, production costs and failure rates of new modules are usually uncertain due to the lack of historical data. Besides, the values of some key parameters in platform design, such as cost saving from designing a modular platform and demand quantity of the products, are also often vague. In this paper, we study the problem of designing a product platform with modularity strategy under fuzzy environment. By characterizing the cost saving from designing a modular platform, the demand quantity of the products and the parameters representing economies of scale and product quality improvement as fuzzy variables, we formulate three fuzzy programming models. An efficient algorithm combining fuzzy simulation and simulated annealing is proposed to solve the models. Numerical experiments are conducted to show the performance of the algorithm.