Judgemental errors in aviation maintenance
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ORIGINAL ARTICLE
Judgemental errors in aviation maintenance Prasanna Illankoon1 · Phillip Tretten1 Received: 6 June 2019 / Accepted: 15 October 2019 © The Author(s) 2019
Abstract Aircraft maintenance is a critical success factor in the aviation sector, and incorrect maintenance actions themselves can be the cause of accidents. Judgemental errors are the top causal factors of maintenance-related aviation accidents. This study asks why judgemental errors occur in maintenance. Referring to six aviation accidents, we show how various biases contributed to those accidents. We first filtered aviation accident reports, looking for accidents linked to errors in maintenance judgements. We analysed the investigation reports, as well as the relevant interview transcriptions. Then we set the characteristics of the actions behind the accidents within the context of the literature and the taxonomy of reasons for judgemental biases. Our results demonstrate how various biases, such as theory-induced blindness, optimistic bias, and substitution bias misled maintenance technicians and eventually become the main cause of a catastrophe. We also find these biases are interrelated, with one causing another to develop. We discuss how these judgemental errors could relate to loss of situation awareness, and suggest interventions to mitigate them. Keywords Judgemental error · Heuristics · Aviation maintenance · Situation awareness
1 Introduction Although their work is mostly “behind the scenes”, aircraft maintenance technicians have an invaluable role in safe aircraft operations, and their errors pose a significant and continuing threat to aviation safety. Maintenance errors have been the cause of numerous tragedies over the course of aviation history. Maintenance technicians are frequently required to make decisions, and “judgemental error” is a leading factor in unsafe maintenance and maintenancerelated aviation accidents (e.g. Schmidt et al. 2000, 2003; Krulak 2004; Rashid et al. 2013; Illankoon et al. 2019a). For example, Krulak (2004) found around 60% of the aircraft mishaps due to maintenance could be traced to errors in human judgement. Studies use Human Factors Analysis and Classification system-Maintenance Extension (HFACS-ME) (Schmidt et al. 1999) and refer to Generic Error-Modelling System (GEMS) (Reason and Hobbs 2003) and skill-based–rule-based–knowledge-based (SRK) models (Rasmussen 1983) to explain causal factors. Although
these methods find judgemental errors leading to maintenance errors, they do not uncover the underlying cognitive mechanisms. Number of recent studies in various domains such as critical disasters (Murata et al. 2015; Brooks et al. 2019; Kinsey et al. 2019), financing (Taylor 2016; Zhang and Cueto 2017; Mittal 2019), scientific research (Baddeley 2015; East 2016), process hazard analysis (Baybutt 2016), clinical practices (Ryan et al. 2018; Dobler et al. 2019), tourist travel (Wattanacharoensil and La-ornual 2019), artificial intelligence (Nelson 2019), traffic accidents (Liu et al. 2019), and proj
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