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Optimizing and Evaluating a Maintenance Strategy for Multi-Component Systems

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Optimization and Data Science: Trends and Applications

Part of the book series: AIRO Springer Series ((AIROSS,volume 6))

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Abstract

Maintenance optimization is a key challenge in engineering and industry. Nowadays, the development of multi-component and complex systems has increased the difficulty of studying and analyzing these systems. Preventive and corrective thresholds are set to check the system deterioration. If one of those thresholds is exceeded by a component, this component is preventively or corrective maintained, depending on its degradation level. The system is periodically inspected, and these inspection times are used as opportunities to perform a preventive maintenance in the rest of the components. The optimal cost, minimizing the time between inspections and the preventive thresholds, is evaluated. Different techniques for the optimization process are employed; typical Monte-Carlo simulation combined with some meta-heuristic algorithms.

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Acknowledgements

This research was supported by Junta de Extremadura, Spain (Project GR18108) and European Union (European Regional Development Funds).

The authors want to thank the anonymous reviewers for their useful comments and time.

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Authors and Affiliations

  1. Department of Mathematics, University of Extremadura, Badajoz, Spain

    Lucía Bautista Bárcena & Inmaculada T. Castro

Authors
  1. Lucía Bautista Bárcena
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  2. Inmaculada T. Castro
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Corresponding author

Correspondence to Lucía Bautista Bárcena .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering and Information Technology, University of Naples “Federico II”, Naples, Italy

    Adriano Masone

  2. Optrail, Rome, Italy

    Veronica Dal Sasso

  3. Faculty of Science and Technology, Free University of Bozen, Bolzano, Italy

    Valentina Morandi

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Bárcena, L.B., Castro, I.T. (2021). Optimizing and Evaluating a Maintenance Strategy for Multi-Component Systems. In: Masone, A., Dal Sasso, V., Morandi, V. (eds) Optimization and Data Science: Trends and Applications. AIRO Springer Series, vol 6. Springer, Cham. https://doi.org/10.1007/978-3-030-86286-2_12

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