Resilience Assessment of Manufacturing Systems With Stepwise Performance Under Disruptions: A Case Study of Blowout Preventer Manufacturing

When disruptions propagate through buffer depletion and batch‐wise repair, many manufacturing systems exhibit stepwise performance degradation and recovery, where output holds constant over periods and drops abruptly at critical events. Conventional resilience metrics, originally developed for systems with continuously varying performance, cannot adequately capture the staged characteristics of such trajectories. To address this, we propose a multi‑dimensional resilience assessment framework tailored to manufacturing systems with stepwise performance. Six indicators are constructed from the time‑recovery curve: absorptive capacity, resistive capacity, restorative capacity, adaptive capacity, performance change, and traditional resilience. Entropy weighting and Euclidean‑distance‑based comparison are used for objective aggregation. A blowout preventer manufacturing system, as a representative case, is simulated under five disruption scenarios. Results show that the framework captures staged disruption‑recovery features more effectively than conventional output‑ratio methods, yielding a comprehensive resilience degree of 67.82% versus 64.78% under simple averaging. Crucially, it reveals that resilience improvement can manifest as delayed degradation, faster recovery organization, and enhanced post‑recovery capability—not merely reduced output loss. A prior prediction model is further integrated to enable forward‐looking resilience estimation, and the prior–posterior comparison reveals that temporal indicators are significantly harder to predict than steady‐state performance, with errors below 2% for the latter but 97.8%–99.5% for resistive capacity, offering diagnostic insight into hidden organizational resilience. The framework provides a resilience‑oriented evaluation approach for a broad class of manufacturing systems with stepwise performance dynamics.