Resilience is a performance measure representing the system ability to survive disruptive events, and the rapidity in restoring system capacity after the disruptive event has occurred. Given the significant impact that disruptive events have in the current strictly interconnected and globalized economy, resilience is gaining an increasing relevance in the supply chain sector. Nevertheless, research on resilience estimation of single production plants has been much scarcer. In order to contribute to fill this gap, in this paper a quantitative method to compute plant resilience is developed with reference to manufacturing plants. The method is presented in a deterministic context but it is easily extended to a probabilistic setting. It allows a direct assessment of the initial capacity loss following a disruptive event, as well as the time-dependent capacity recovery path and the connected economic loss due to capacity reconstruction and business interruption. The model can act as a decision support tools for facility designers and emergency managers, and may constitute a building block for more extended models aimed at estimating resilience of whole supply chains.
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