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Probabilistic Evaluation of Product Development Task Planning Using Worth Flow Analysis

[+] Author Affiliations
Toshiharu Miwa

Hitachi, Ltd., Yokohama, Japan

Hideki Aoyama

Keio University, Yokohama, Japan

Kosuke Ishii

Stanford University, Stanford, CA

Paper No. DETC2008-49142, pp. 227-235; 9 pages
  • ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 5: 13th Design for Manufacturability and the Lifecycle Conference; 5th Symposium on International Design and Design Education; 10th International Conference on Advanced Vehicle and Tire Technologies
  • Brooklyn, New York, USA, August 3–6, 2008
  • Conference Sponsors: Design Engineering Division and Computers in Engineering Division
  • ISBN: 978-0-7918-4329-1 | eISBN: 0-7918-3831-5
  • Copyright © 2008 by ASME


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.

Copyright © 2008 by ASME



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