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Optimal Scheduling of Preventive Maintenance for Safety Instrumented Systems Based on Mixed-Integer Programming

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Abstract

Preventive maintenance is essential to guarantee the reliability of the safety instrumented systems in the process industry. The safety integrity level of the safety instrumented systems is evaluated based on the probability of failure on demand, which is significantly influenced by preventive maintenance. In this paper, we give an approach to optimize the schedule of the preventive maintenance for the safety instrumented systems, which considers not only the time instants but also the sequence of the maintenance schedule. The basic idea is to discretize the continuous-time Markov model from the viewpoint of maintenance and then reformulate the problem as a mixed-integer programming problem. Examples are given to illustrate the proposed approach.

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Authors and Affiliations

  1. Institute of Automatic Control, Faculty of Electrical and Computer Engineering, Technische Universität Kaiserslautern, 67663, Kaiserslautern, Germany

    Anas Abdelkarim & Ping Zhang

Authors
  1. Anas Abdelkarim
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  2. Ping Zhang
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Corresponding author

Correspondence to Ping Zhang .

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Editors and Affiliations

  1. Siemens AG, Munich, Bayern, Germany

    Marc Zeller

  2. University of Applied Sciences Rosenheim, Rosenheim, Germany

    Kai Höfig

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Abdelkarim, A., Zhang, P. (2020). Optimal Scheduling of Preventive Maintenance for Safety Instrumented Systems Based on Mixed-Integer Programming. In: Zeller, M., Höfig, K. (eds) Model-Based Safety and Assessment. IMBSA 2020. Lecture Notes in Computer Science(), vol 12297. Springer, Cham. https://doi.org/10.1007/978-3-030-58920-2_6

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  • DOI: https://doi.org/10.1007/978-3-030-58920-2_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58919-6

  • Online ISBN: 978-3-030-58920-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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