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Probability of User Fit for Spatially Optimized Products

[+] Author Affiliations
Christopher Garneau, Matthew Parkinson

Penn State University, University Park, PA

Paper No. DETC2011-48569, pp. 221-229; 9 pages
doi:10.1115/DETC2011-48569
From:
  • ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 5: 37th Design Automation Conference, Parts A and B
  • Washington, DC, USA, August 28–31, 2011
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5482-2
  • Copyright © 2011 by ASME

abstract

This study offers a new method for understanding the likelihood of acceptable fit for users of adjustable products and environments and is a useful tool for aiding the designer in making decisions about problems involving human variability. Accommodation, which describes the ability of a user to interact with a device or environment in a preferred way, is a key product performance metric. Methods that offer a better understanding of accommodation of broad user populations would allow for the design of products that are more cost-effective, safer, and/or lead to greater levels of customer satisfaction. This work uses parametric studies to explore the characteristics of a target user population and the probability of accommodating individuals of a given body size. Performance regions are identified in both the problem’s design space (the product dimensions under consideration) and the anthropometry space of the target population (the relevant body dimensions of product users). The existence of probability contours is a result of outcome uncertainty due to anthropometry-independent user preference, and the analysis is achieved by assessing binary accommodation of individuals using a “virtual fit” method with many iterations. Two case studies, one univariate and one bivariate in both performance and anthropometry spaces, are presented. An important outcome of the decision making framework described in this work is the ability to intuitively gauge who in the population of target users will be disaccommodated by a design and how to improve overall accommodation.

Copyright © 2011 by ASME
Topics: Probability

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