Abstract
This paper describes and evaluates the boundary case methodology for the simultaneous consideration of variance for a number of selected anthropometric variables. The methodology includes the calculation of key dimension values for extreme but likely anthropometric measurement combinations. This data can be applied when utilising digital human modelling (DHM) tools for proactive design work and entered as input data when representative manikins are defined. The mathematical procedure is clearly described and exemplified to demonstrate how to use the methodology in design work. The outcome of the method is illustrated and compared using several different cases where the number of measurements is varied and where principal component analysis (PCA) is used to reduce the number of dimensions in one case. The paper demonstrates that the proposed boundary case method is advantageous compared to approaches based on the use of univariate percentile data in design.
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