Fink, L., Matyas, G., Zink, F., Wallner, B., Bleicher, F., & Trautner, T. (2025). Severity of Failure: Resilience Assessment on the Shop Floor. In S. Thiede, R. Damgrave, T. Vanekar, & E. Lutters (Eds.), 58th CIRP Conference on Manufacturing Systems 2025 (pp. 85–90). Elsevier B. V. https://doi.org/10.1016/j.procir.2025.03.008
58th CIRP Conference on Manufacturing Systems 2025
-
Volume:
134
-
Date (published):
2025
-
Event name:
58th CIRP Conference on Manufacturing Systems 2025 (CIRP CMS 2025)
en
Event date:
14-Apr-2025 - 16-Apr-2025
-
Event place:
Netherlands (the)
-
Number of Pages:
6
-
Publisher:
Elsevier B. V.
-
Peer reviewed:
Yes
-
Keywords:
Assessment; Manufacturing; Resilience; Shop Floor
en
Abstract:
Shop floor operations are affected by uncertainties and disruptions. These can come from the supply chain causing shortages of materials, worker unavailability due to, e.g., unforeseen pandemics, and spontaneous machine breakdowns. To address these challenges, resilient manufacturing systems are essential. However, there is a lack of practical methods for quantifying how well a shop floor withstands and recovers from such disruptions and assessing its level of resilience. Therefore, we propose a new approach for evaluating the resilience of the shop floor by assessing the production schedule and its underlying scheduler. Our Severity of Failure (SoF) method assesses each scheduled task by calculating the impact of its failure on the entire production schedule and combining it with the probability of the failure occurring. The method has been validated by assessing production schedules generated by various dispatching rules, demonstrating both its practical applicability and its potential to evaluate the resilience of different scheduling algorithms. Furthermore, the beneficial effect of buffer times on resilience was also evaluated.
en
Project title:
FLEX4RES – Data spaces for flexible production lines and supply chains for resilient manufacturing: 101091903 (European Commission)
-
Research Areas:
Digital Transformation in Manufacturing: 80% Efficient Utilisation of Material Resources: 10% Modeling and Simulation: 10%