Skip to main content
SpringerLink
Log in

Efficient Simulation Approaches for Reliability Analysis of Large Systems

  • Conference paper
  • First Online:
Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 610))

Abstract

Survival signature has been presented recently to quantify the system reliability. However, survival signature-based analytical methods are generally intractable for the analysis of realistic systems with multi-state components and imprecisions on the transition time. The availability of numerical simulation methods for the analysis of such systems is required. In this paper, novel simulation methods for computing system reliability are presented. These allow to estimate the reliability of realistic and large-scale systems based on survival signature including parameter uncertainties and imprecisions. The simulation approaches are generally applicable and efficient since only one estimation of the survival signature is needed while Monte Carlo simulation is used to generate component transition times. Numerical examples are presented to show the applicability of the proposed methods.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Alvarez, D.A.: Infinite random sets and applications in uncertainty analysis. Ph.D. thesis, Arbeitsbereich für Technische Mathematik am Institut für Grundlagen der Bauingenieurwissenschaften. Leopold-Franzens-Universität Innsbruck, Innsbruck, Austria (2007) https://sites.google.com/site/diegoandresalvarezmarin/RSthesis.pdf

  2. Alvarez, D.A., Hurtado, J.E.: An efficient method for the estimation of structural reliability intervals with random sets, dependence modelling and uncertain inputs. Comput. Struct. 142, 54–63 (2014)

    Article  Google Scholar 

  3. Aslett, L.J.M. : MCMC for Inference on Phase-type and Masked System Lifetime Models. Ph.D. thesis, Trinity College Dublin (2012)

    Google Scholar 

  4. Aslett, L.J.M.: Reliabilitytheory: Tools for structural reliability analysis. r package (2012)

    Google Scholar 

  5. Beer, M., Patelli, E.: Editorial: Engineering analysis with vague and imprecise information. Structural Safety Special Issue: Engineering Analyses with Vague and Imprecise Information 52, Part B(0), 143 (2015)

    Google Scholar 

  6. Butler, J., Jia, J., Dyer, J.: Simulation techniques for the sensitivity analysis of multi-criteria decision models. Eur. J. Oper. Res. 103(3), 531–546 (1997)

    Article  MATH  Google Scholar 

  7. Coolen, F.P.A., Coolen-Maturi, T.: Generalizing the signature to systems with multiple types of components. In: Zamojski, W., Mazurkiewicz, J., Sugier, J., Walkowiak, T., Kacprzyk, J. (eds.) Complex Systems and Dependability. AISC, vol. 170, pp. 115–130. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  8. Coolen, F.P.A., Coolen-Maturi, T.: Modelling uncertain aspects of system dependability with survival signatures. In: Zamojski, W., Sugier, J. (eds.) Dependability Problems of Complex Information Systems. AISC, vol. 307, pp. 19–34. Springer, Heidelberg (2014)

    Google Scholar 

  9. Arthur, P.: Dempster.: Upper and lower probabilities induced by a multivalued mapping. Annal. Math. Stat. 38, 325–339 (1967)

    Article  Google Scholar 

  10. Feng, G., Patelli, E., Beer, M., Coolen, F.: Imprecise system reliability and component importance based on survival signature. Reliab. Eng. Syst. Saf. 150, 116–125 (2016)

    Article  Google Scholar 

  11. Kołowrocki, K., Kwiatuszewska-Sarnecka, B.: Reliability and risk analysis of large systems with ageing components. Reliab. Eng. Syst. Saf. 93(12), 1821–1829 (2008)

    Article  Google Scholar 

  12. Modarres, M.: What Every Engineer Should Know About Reliability and Risk Analysis, vol. 30. CRC Press, Boca Raton (1992)

    Google Scholar 

  13. Patelli, E., Alvarez, D.A., Broggi, M., de Angelis, M.: Uncertainty management in multidisciplinary design of critical safety systems. J. Aerosp. Inf. Syst. 12, 140–169 (2015)

    Google Scholar 

  14. Patelli, E., Broggi, M., de Angelis Marco, M.B.: OpenCossan: An efficient open tool for dealing with epistemic and aleatory uncertainties. In: Vulnerability, Uncertainty, and Risk, pp. 2564–2573. American Society of Civil Engineers, June 2014

    Google Scholar 

  15. Rubinstein, R.Y.: Optimization of computer simulation models with rare events. Eur. J. Oper. Res. 99(1), 89–112 (1997)

    Article  Google Scholar 

  16. Samaniego, F.J.: System Signatures and Their Applications in Engineering Reliability, vol. 110. Springer Science & Business Media, New York (2007)

    MATH  Google Scholar 

  17. Shafer, G.: A Mathematical Theory of Evidence. Princeton University Press, Princeton (1976)

    MATH  Google Scholar 

  18. Zanakis, S.H., Solomon, A., Wishart, N., Dublish, S.: Multi-attribute decision making: A simulation comparison of select methods. Eur. J. Oper. Res. 107(3), 507–529 (1998)

    Article  MATH  Google Scholar 

  19. Zio, E., Baraldi, P., Patelli, E.: Assessment of the availability of an offshore installation by Monte Carlo simulation. Int. J. Press. Vessels Pip. 83(4), 312–320 (2006)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute for Risk and Uncertainty, University of Liverpool, Chadwick Building, Peach Street, Liverpool, L69 7ZF, UK

    Edoardo Patelli & Geng Feng

Authors
  1. Edoardo Patelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Geng Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Edoardo Patelli .

Editor information

Editors and Affiliations

  1. INESC-ID,Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal

    Joao Paulo Carvalho

  2. LIP 6, Université Pierre et Marie Curie, Paris, France

    Marie-Jeanne Lesot

  3. School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands

    Uzay Kaymak

  4. IDMEC,Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal

    Susana Vieira

  5. LIP6, Université Pierre et Marie Curie, CNRS, Paris, France

    Bernadette Bouchon-Meunier

  6. Machine Intelligence Institute, Iona College, New Rochelle, New York, USA

    Ronald R. Yager

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Patelli, E., Feng, G. (2016). Efficient Simulation Approaches for Reliability Analysis of Large Systems. In: Carvalho, J., Lesot, MJ., Kaymak, U., Vieira, S., Bouchon-Meunier, B., Yager, R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2016. Communications in Computer and Information Science, vol 610. Springer, Cham. https://doi.org/10.1007/978-3-319-40596-4_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-40596-4_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40595-7

  • Online ISBN: 978-3-319-40596-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation