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Sensitivity Analysis of Relative Worth in Empirical and Simulation-Based QFD Matrices

[+] Author Affiliations
Robins M. Kalapurackal, Shun Takai

Missouri University of Science and Technology, Rolla, MO

Paper No. DETC2008-49861, pp. 149-158; 10 pages
doi:10.1115/DETC2008-49861
From:
  • 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

abstract

Quality function deployment (QFD) is one of the most popular tools used in the product development process. It relates customer requirements to product requirements and enables engineers to determine which product requirement is more important than the others in satisfying customers. Some of the benefits of QFD are cost reduction, fewer design changes at the start of production, and improved communication among engineers. QFD applications use various approaches (i.e., worth calculation schemes and rating scales) to calculate the worth of requirements. The purpose of this paper is to study the change in the relative worth (normalized worth) of product requirements yielded by different rating scales and calculation schemes. We studied empirical and simulation-generated QFD matrices to determine how calculation schemes and rating scales influence the relative worth of requirements. Two representative scales and two calculation schemes are used to find the most and least sensitive cases, and the influence of the number of rows and columns in the relative worth of requirements. From the results, we identified the least sensitive and most sensitive combination of calculation scheme and rating scale. We also learned that QFD matrices become less sensitive to changes in rating scale and calculation scheme as the number of columns increases.

Copyright © 2008 by ASME

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