Use of Cognitive Task Analysis to Inform Future Research and Identify Solutions for Haul Truck Safety
Public Domain
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2022/02/27
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Series: Mining Publications
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Description:Each year, haul truck accidents account for a large portion of mining injuries and fatalities. To better understand why these accidents continue to occur, researchers from the National Institute for Occupational Safety and Health (NIOSH) utilized a cognitive task analysis methodology to identify the user requirements of surface haul truck operators and assess differences in perceptions between operators, managers, health and safety professionals, trainers, and maintenance personnel. Additionally, researchers used the critical decision method to focus on better understanding the cognitive demands, decision-making, and problem solving during nonroutine incidents. The preliminary results of this study identify and explore themes within the broad categories of hazards, skills & expertise, and training and provide detailed accounts of nonroutine incidents such as near-misses, loss of control, and collisions. These accounts reveal insights into operator decision making and event progressions that can then be used to build more realistic training scenarios and address hidden hazards and root causes of these incidents. These results, along with potential solutions offered by study participants, can inform future research and help identify creative interventions that can be used by mine operators to address haul truck safety issues. [Description provided by NIOSH]
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ISBN:9781713845089
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Pages in Document:37-43
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NIOSHTIC Number:nn:20065286
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Citation:MineXchange: 2022 SME Annual Conference and Expo, February 27-March 2, 2022, Salt Lake City, Utah, preprint 22-009. Englewood, CO: Society for Mining, Metallurgy & Exploration, 2022 Feb; :37-43
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Federal Fiscal Year:2022
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Peer Reviewed:False
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Source Full Name:MineXchange: 2022 SME Annual Conference and Expo, February 27-March 2, 2022, Salt Lake City, Utah, preprint 22-009
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Main Document Checksum:urn:sha-512:373c26476deb9fa88aa4a8ed7b271247d61007281b544088b26cf4a267ce12bcc6dc241d6772eb7a180593aebb1ff9b67b8ca0da985252d15d4d9aaa3affe97a
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