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Optimization of tool handle shape for a target user population

Optimization of tool handle shape for a target user population

by mbp11 | Aug 30, 2009 | Publications

One goal of Designing for Human Variability (DfHV) is to optimize the interaction between user and device. Often, this interaction is dictated by the spatial dimensions or shape of the artifacts with which people interact. A novel approach that applies DfHV principles...
Modeling variability in torso shape for chair and seat design

Modeling variability in torso shape for chair and seat design

by mbp11 | Aug 3, 2008 | Publications

Anthropometric data are widely used in the design of chairs, seats, and other furniture intended for seated use. These data are valuable for determining the overall height, width, and depth of a chair, but contain little information about body shape that can be used...
Improved head restraint design for safety and compliance

Improved head restraint design for safety and compliance

by mbp11 | Sep 10, 2006 | Publications

The National Highway Traffic Safety Administration (NHTSA) recently revised Federal Motor Vehicle Safety Standard (FMVSS) 202, which governs head restraints. The new standard, known as FMVSS 202a, establishes for the first time in the U.S. a requirement for the...
Robust truck cabin layout optimization using advanced driver variance models

Robust truck cabin layout optimization using advanced driver variance models

by mbp11 | Sep 24, 2005 | Publications

One important source of variance in the performance and success of products designed for use by people is the people themselves. In many cases, the acceptability of the design is affected more by the variance in the human users than by the variance attributable to the...
Improving an ergonomics testing procedure via approximation-based adaptive experimental design

Improving an ergonomics testing procedure via approximation-based adaptive experimental design

by mbp11 | Dec 12, 2004 | Publications

Adaptive design refers to experimental design where the next sample point is determined by information from previous experiments. This article presents a constrained optimization algorithm known as superEGO (a variant of the EGO algorithm of Schonlau, Welch, and...
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