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Predicting availability functions in time-dependent complex systems with SAEDES simulation algorithms

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  • Faulin, Javier
  • Juan, Angel A.
  • Serrat, Carles
  • Bargueño, Vicente

Abstract

In this paper, we propose the use of discrete-event simulation (DES) as an efficient methodology to obtain estimates of both survival and availability functions in time-dependent real systems—such as telecommunication networks or distributed computer systems. We discuss the use of DES in reliability and availability studies, not only as an alternative to the use of analytical and probabilistic methods, but also as a complementary way to: (i) achieve a better understanding of the system internal behavior and (ii) find out the relevance of each component under reliability/availability considerations. Specifically, this paper describes a general methodology and two DES algorithms, called SAEDES, which can be used to analyze a wide range of time-dependent complex systems, including those presenting multiple states, dependencies among failure/repair times or non-perfect maintenance policies. These algorithms can provide valuable information, specially during the design stages, where different scenarios can be compared in order to select a system design offering adequate reliability and availability levels. Two case studies are discussed, using a C/C++ implementation of the SAEDES algorithms, to show some potential applications of our approach.

Suggested Citation

  • Faulin, Javier & Juan, Angel A. & Serrat, Carles & Bargueño, Vicente, 2008. "Predicting availability functions in time-dependent complex systems with SAEDES simulation algorithms," Reliability Engineering and System Safety, Elsevier, vol. 93(11), pages 1761-1771.
    • Handle: RePEc:eee:reensy:v:93:y:2008:i:11:p:1761-1771
    DOI: 10.1016/j.ress.2008.03.022
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    References listed on IDEAS

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    1. John J. McCall, 1965. "Maintenance Policies for Stochastically Failing Equipment: A Survey," Management Science, INFORMS, vol. 11(5), pages 493-524, March.
    2. Cho, Danny I. & Parlar, Mahmut, 1991. "A survey of maintenance models for multi-unit systems," European Journal of Operational Research, Elsevier, vol. 51(1), pages 1-23, March.
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    Cited by:

    1. Alejandro Estrada-Moreno & Albert Ferrer & Angel A. Juan & Javier Panadero & Adil Bagirov, 2020. "The Non-Smooth and Bi-Objective Team Orienteering Problem with Soft Constraints," Mathematics, MDPI, vol. 8(9), pages 1-16, September.
    2. Juan, Angel A. & Faulin, Javier & Grasman, Scott E. & Rabe, Markus & Figueira, Gonçalo, 2015. "A review of simheuristics: Extending metaheuristics to deal with stochastic combinatorial optimization problems," Operations Research Perspectives, Elsevier, vol. 2(C), pages 62-72.
    3. Diego Oliva & Pedro Copado & Salvador Hinojosa & Javier Panadero & Daniel Riera & Angel A. Juan, 2020. "Fuzzy Simheuristics: Solving Optimization Problems under Stochastic and Uncertainty Scenarios," Mathematics, MDPI, vol. 8(12), pages 1-19, December.
    4. Christopher Bayliss & Marti Serra & Armando Nieto & Angel A. Juan, 2020. "Combining a Matheuristic with Simulation for Risk Management of Stochastic Assets and Liabilities," Risks, MDPI, vol. 8(4), pages 1-14, December.
    5. Juliana Castaneda & Xabier A. Martin & Majsa Ammouriova & Javier Panadero & Angel A. Juan, 2022. "A Fuzzy Simheuristic for the Permutation Flow Shop Problem under Stochastic and Fuzzy Uncertainty," Mathematics, MDPI, vol. 10(10), pages 1-17, May.

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