The acceleration of the product development cycle continues to be a significant challenge for manufacturing firms around the world. The present paper describes a task planning method that takes the uncertain relationships among the product components into consideration in order to reduce the development time in large-scale and complicated product development with uncertainty at the early stage of product development. We developed a probabilistic worth flow analysis to evaluate each product component for task prioritization with an uncertain relationship among product components. The method calculates the probabilistic distribution of worth flow of each product component based on the probabilistic relationship among product components with the Monte Carlo simulation and determines the development sequence of each component so as to minimize the possibility with the highest feedback information across the task groups. The present paper describes an example of a generic hair drier with a simple mechanical structure developed using the proposed method in order to reduce the uncertainty of feedback information across the task groups while maintaining the uncertainty within same task groups in case the uncertainty has an asymmetric distribution.

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