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Assessing the effects of slippery steel beam coatings to ironworkers' gait stability : Assessing the effects of slippery steel beam coatings to ironworkers gait stability

Cited 25 time in Web of Science Cited 25 time in Scopus
Authors

Kim, Hyunsoo; Ahn, Changbum R.; Stentz, Terry L.; Jebelli, Houtan

Issue Date
2018-04
Publisher
Pergamon Press Ltd.
Citation
Applied Ergonomics, Vol.68, pp.72-79
Abstract
Since ironworkers walk and perform their tasks on steel beams, identifying the effects of slippery steel beam surfaces on ironworkers gait stability—which can be related to safety risk—is critical. However, there is no accepted or validated standard for measuring the slipperiness of coated steel beams, which makes evaluating and controlling for slipperiness a challenge. In this context, this study investigated the effect of the slipperiness of steel beam coatings on ironworkers gait stability. Accordingly, to identify the relationships between coefficient of friction, perceived slipperiness, and gait stability—represented as the Maximum Lyaponuv exponent (Max LE)—an experiment was conducted with eight different surfaces and sixteen subjects with varying experience as ironworkers. The experiment's results indicate that the slipperiness of the various surfaces greatly affect ironworkers gait stability while they walk on coated steel beam surfaces. In detail, the Max LE of two subject groups—experienced and inexperienced ironworkers—highly correlated with both the dynamic coefficient of friction values measured by following ANSI B101.3 and with the subjective rating scores of the inexperienced subject group. Unlike subjective rating scores—which were particularly incongruent among experienced workers—the Max LE of inexperienced and experienced subjects has a consistent pattern. This study result highlights an opportunity for using gait stability measurements to quantify and differentiate the safety risks caused by slippery coated steel beams in the future.
ISSN
0003-6870
URI
https://hdl.handle.net/10371/203257
DOI
https://doi.org/10.1016/j.apergo.2017.11.003
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  • College of Engineering
  • Department of Architecture & Architectural Engineering
Research Area Computing in Construction, Management in Construction

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