A Simulation-Based Evaluation of Dynamic Task Prioritization in Maintenance Management

Research output: Contribution to conferenceAbstractpeer-review


Availability of machines is crucial to be an efficient manufacturer and well organized maintenance operations are key to success. Due to the advancement of condition monitoring and predictive analytics the field shifts more and more from corrective to preventive task fulfillment. Nevertheless, especially in automotive production lines trained experts are rare and responsible for many machines simultaneously. As a consequence, the scheduling of corrective and preventive tasks significantly influences the performance of the production system. Despite the fact that researchers have already identified this correlation,
merely straightforward heuristics are used in practice. Yet, these algorithms ensure an acceptable output of production lines, but the question arises if their performance could be further improved, by utilizing algorithms for dynamic bottleneck detection. Therefore, a conducted simulation study determines the reliability of selected bottleneck detection algorithms and evaluates their applicability to prioritize repair tasks. Multiple algorithms have been evaluated in course of this study. Results show that the Active Period Method outperforms simple adhoc heuristics and also other algorithms from literature. Further, the
dynamic bottleneck ranking proves to be a suitable method to prioritize repair orders.
Original languageEnglish
Publication statusPublished - Jul 2018
Event29th European Conference on Operational Research - UPV Universitat Politècnica de València, Valencia, Spain
Duration: 8 Jul 201811 Jul 2018


Conference29th European Conference on Operational Research
Abbreviated titleEURO2018
Internet address


  • Simulation
  • Maintenance Management


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