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Predictive Maintenance Model with Dependent Stochastic Degradation Function Components

  • Janusz SzpytkoEmail author
  • Yorlandys Salgado DuarteEmail author
Conference paper
  • 6 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11878)

Abstract

The paper presents an Integrated Maintenance Decision Making Model (IMDMM) concept for cranes under operation with dependent stochastic function into the container type terminals. The target is to improve cranes operational efficiency through minimizing the risk of the Gantry Cranes Inefficiency (GCI) results based on implementation of copula approach model for stochastic degradation function dependency between cranes. In the present study, we investigate the influence of dependent stochastic degradation of multiple cranes on the optimal maintenance decisions. We use copula to model the dependent stochastic degradation of components and we formulate the optimal decision problem based on the minimum GCI expected. We illustrate the developed probabilistic analysis approach and the influence of the dependency of the stochastic degradation on the preferred decisions through numerical examples, and we discuss the close relationship of this approach with interoperability concepts. The crane operation risk is estimated with a sequential Monte Carlo Markov Chain (MCMC) simulation model and the optimization model behind of IMDMM is supported through the Particle Swarm Optimization (PSO) algorithms.

Keywords

Maintenance Copula approach Stochastic optimization 

Notes

Acknowledgement

The work has been financially supported by the Polish Ministry of Science and Higher Education.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.AGH University of Science and TechnologyKrakowPoland

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