Browsing by Author "Green, Richard N."

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    Engineering maintenance decision-making with unsupported judgement under operational constraints
    (Elsevier, 2022-05-10) Green, Richard N.; McNaught, Ken R.; Saddington, Alistair J.
    In 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.
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    Supporting operational decision making concerning aircraft structural integrity damage identified during maintenance.
    (2021-06) Green, Richard N.; McNaught, Ken R.; Saddington, Alistair J.
    Military aircraft operations balance delivery pressures and engineering risks. Aircraft structural damage incurred in-service creates complex risk decision problems for managers deliberating maintenance activity such as delaying rectification to continue operations, or grounding an aircraft or entire fleet. In many operational settings, aircraft availability demands restrict the time, information, or resources to analyse structural risks, making formal risk or decision analysis intractable. Exact solutions are information intensive and require specialist knowledge or machinery beyond the capabilities of generalist engineering managers, often compelling decision-makers to use their subjective judgement in an unsupported way. For actors deliberating aircraft maintenance structural risks in such circumstances, a novel approach based upon heuristics, argument and bounded rationality is proposed, which was informed by the results from a survey of engineering practitioners and case study analyses. Testing of the approach was carried-out with 21 aircraft engineering decision-makers with experience of structural integrity risks, split into three groups, using realistic but fictional textual simulations of aircraft maintenance. One group used existing decision justification approaches and were compared with a second group who provided decision justifications using the novel approach. Users of the novel approach felt supported and were very confident in their justifications. The third group of raters comparing the two sets of decision justifications indicated preferences using Likert scales against the criteria: which is easier to understand, which is more transparent, and which gives the better justification. Analysis of the comparative results iii ABSTRACT iv using ANOVA provided evidence that the novel approach enabled better decision justification and transparency compared to existing approaches. The novel approach aids decision-makers compelled to use their unsupported subjective judgement, improving organisational resilience by improving robustness and stretching system process to handle surprises, and providing a clear record of the decision basis for post hoc review