The role of univariate and multivariate data in the design of advanced operator workstations

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Cerney, Melinda
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Mechanical Engineering
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The application of human figure data in workstation design has typically relied on "traditional" anthropometric data-length, breadth, width, and height values recorded when the subject is positioned in standard, erect anthropometric postures. In spite of the increasing availability of three-dimensional data, many human factors and ergonomics decisions continue to be based upon these univariate anatomical measures through the use of summary statistics such as the 95th percentile seated eye height or generalized design cases like the 5th percentile female. These methods simplify the representation of a population with a collection of one-dimensional measurements which fail to maintain the form information or homology of the original subjects. This thesis explores the use of three-dimensional landmark data as a more complete method of representing the human form, through * statistical comparison of the characteristics of traditional, univariate anthropometric data to three-dimensional anthropometric data, and * description of the development of an immersive, virtual reality application used to design operator workstations based on 3D anthropometric data. Traditional distance data extracted from the 3D data set, and three-dimensional landmark data are compared through an array of statistical and multivariate methods to explore whether subjective posturing hinders design methods and whether the distillation of three-dimensional landmark data to distance measurements is capable of maintaining a subject's true form for the purposes of design. An advanced operator workstation tool is detailed which allows for the use and examination of three-dimensional landmark data, body scans, and motion paths relative to a workstation design in an immersive, virtual reality environment.

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Wed Jan 01 00:00:00 UTC 2003