Estimating resilience of manufacturing plants to physical disruptions: Model and application

A.C. Caputo, L. Donati and P. Salini

International Journal of Production Economics, 2023, vol. 266, issue C

Abstract: The concept of Resilience is gaining an increasing importance in industrial systems, service networks and supply chains, as it extends traditional risk assessment methods by capturing both shortterm and long-term effects of accidents and disruptions. Resilience is, in fact, both a qualitative property and a performance indicator that measures the system's ability to survive disruptive events, and rapidly restore its functionality after the disruptive event has occurred. However, while literature about systems resilience is ample, comparatively scarce attention has been devoted to the evaluation of production systems resilience. As a contribution to fill this gap, in this paper a quantitative method for resilience estimation specifically aimed at manufacturing plants is developed. The method focuses on computing resilience of the manufacturing process, according to its structure, when resources are subjected to physical damage resulting from disruptive events such as sabotage, technical accidents or natural disasters. Overall, the paper allows to assess the economic loss and duration of production interruption in any kind of manufacturing plant when subjected to damage produced by the above causes. In particular, the method enables direct assessment of the initial capacity loss following a prescribed disruptive event, and explicit estimation of the time-dependent capacity recovery path based on the actual process structure and sequence of resources restoration tasks, also allowing the quantification of resulting economic losses. In the paper, after model development, an application example is provided to show model capabilities. Facility designers and emergency managers can use this model as a decision support tool for risk assessment, and to plan emergency actions and plant refurbishment aimed at resilience enhancement.

Keywords: Manufacturing plant; Resilience; Disruption; Business interruption; Mathematical model; Capacity recovery (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:266:y:2023:i:c:s0925527323002694

DOI: 10.1016/j.ijpe.2023.109037

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