Engineering maintenance decision-making with unsupported judgement under operational constraints

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dc.contributor.authorGreen, Richard N.
dc.contributor.authorMcNaught, Ken R.
dc.contributor.authorSaddington, A. J.
dc.date.accessioned2022-05-18T13:05:45Z
dc.date.available2022-05-18T13:05:45Z
dc.date.issued2022-05-10
dc.description.abstractIn operational engineering maintenance situations, limitations on time, resource or the information available often inhibit rigorous analysis on complex decision problems. Decision-makers who are compelled to act in such circumstances, may be informed by some level of analysis if available, or else may have to rely on their unsupported judgement. This paper presents three engineering risk decision-making case studies across a 20 year span from the rail, aerospace, and military aviation contexts, highlighting the fallibilities of using unsupported judgements in an unstructured manner. To help situate this type of decision situation, we provide a descriptive model of the decision space which extends an existing description from the discipline of decision analysis. Furthermore, to help make and describe the distinction between unsupported and supported thinking, we provide another descriptive model, this time drawing parallels with the distinction made between Type 1 and Type 2 reasoning. This model is an extension of the default-interventionist model from cognitive psychology. The paper concludes that there is a pressing need to provide some form of support to engineering decision-makers facing operational decisions under severe time pressure. While the ultimate aim must be to improve the quality of decision-making, improved transparency is an important additional benefit. Increased emphasis on decision justification and self-awareness are suggested as potential ways of improving this situation. A further contribution of this paper is to identify and strengthen linkages between safety science and two other relevant disciplines, decision analysis and psychology. Such linkages make it easier to communicate across traditional disciplinary boundaries and may provide opportunities for interdisciplinary learning or suggest future directions for collaborative research.en_UK
dc.identifier.citationGreen RN, McNaught KR, Saddington AJ. (2022) Engineering maintenance decision-making with unsupported judgement under operational constraints, Safety Science, Volume 153, September 2022, Article number 105756en_UK
dc.identifier.issn0925-7535
dc.identifier.urihttps://doi.org/10.1016/j.ssci.2022.105756
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/17911
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectDecision-makingen_UK
dc.subjectRisk assessmenten_UK
dc.subjectOperational risken_UK
dc.subjectDual process theoryen_UK
dc.subjectJudgementen_UK
dc.subjectEngineering maintenanceen_UK
dc.titleEngineering maintenance decision-making with unsupported judgement under operational constraintsen_UK
dc.typeArticleen_UK

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