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A prospective study of maintenance deviations using HFACS-ME
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. (Human Factors)ORCID iD: 0000-0001-8693-3431
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0003-3827-0295
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
2019 (English)In: International Journal of Industrial Ergonomics, ISSN 0169-8141, E-ISSN 1872-8219, Vol. 74, article id 102852Article in journal (Refereed) Published
Abstract [en]

The factors initiating aviation accidents are usually hidden behind various steps, systems, and tasks, and systematic root-cause analysis is required to uncover the initial factor(s). To reduce the risk of unfavourable events, it is more appropriate to study their causal factors. We argue that an in-depth study on maintenance process deviations could assist in uncovering hidden causal factors. We therefore analyse reported maintenance deviations from an aviation organisation using the Human Factor Analysis and Classification System-Maintenance Extension (HFACS-ME) taxonomy to aggregate and map hidden causal factors. We find attention and memory errors and inadequacy of processes and documentation are major causal factors. We argue a well-run organisation can capture hidden causal factors and reduce the risk of incidents and accidents. More specifically, we show how situation awareness (SA) interventions can assist in the mitigation of maintenance deviations and capture hidden causal factors.

Place, publisher, year, edition, pages
Elsevier, 2019. Vol. 74, article id 102852
Keywords [en]
Aviation maintenance, Incidents, Active error, Latent condition, Situation awareness
National Category
Production Engineering, Human Work Science and Ergonomics Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-76338DOI: 10.1016/j.ergon.2019.102852OAI: oai:DiVA.org:ltu-76338DiVA, id: diva2:1359706
Funder
Luleå Railway Research Centre (JVTC), 167522
Note

Validerad;2019;Nivå 2;2019-10-15 (johcin)

Available from: 2019-10-10 Created: 2019-10-10 Last updated: 2019-10-15Bibliographically approved

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Illankoon, PrasannaTretten, PhillipKumar, Uday

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