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contributor authorTechera Ulises;Hallowell Matthew;Littlejohn Ray;Rajendran Sathyanarayanan
date accessioned2019-02-26T07:39:42Z
date available2019-02-26T07:39:42Z
date issued2018
identifier other%28ASCE%29CO.1943-7862.0001513.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4248563
description abstractThe increasing commitment to safety over the last two decades has contributed to a 67% decline in recordable incident rates. The rate of fatalities, however, has recently increased. Human factors, like fatigue, strongly relate to fatalities. The prediction of fatigue would allow for an early intervention, thus mitigating safety risk. The literature suggests several potential predictors of fatigue onset; however, each of these was mainly studied in isolation, in laboratory settings, and their predictive validity in the construction industry remains unknown. The authors hypothesized that a set of measurable factors can predict construction worker fatigue. A field study of 252 US construction workers was conducted in which potential predictors and fatigue levels were assessed, and the first fatigue predictive models for construction workers were created. The models presented low to medium predictivity, demonstrating that laboratory research and results obtained from other occupations do not directly apply to the construction industry. Furthermore, fatigue predictive models showed to differ among trades. These models will serve the industry to better manage fatigue; however, further research in this area is needed.
publisherAmerican Society of Civil Engineers
titleMeasuring and Predicting Fatigue in Construction: Empirical Field Study
typeJournal Paper
journal volume144
journal issue8
journal titleJournal of Construction Engineering and Management
identifier doi10.1061/(ASCE)CO.1943-7862.0001513
page4018062
treeJournal of Construction Engineering and Management:;2018:;Volume ( 144 ):;issue: 008
contenttypeFulltext


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