Skip to main content

Common Cause Failure Modeling: Status and Trends

  • Chapter
Handbook of Performability Engineering

Abstract

This chapter presents a status of common cause failure (CCF) modeling. The well known betafactor model is still the most commonly used CCF model. The strengths and limitations of this model are therefore outlined together with approaches to establish plant specific beta-factors. Several more advanced CCF models are also described with a special focus on the new multiple beta-factor model. Problems relating to data availability and estimation of the unknown parameters of the various models are discussed, and ideas for further research are suggested.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 429.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 549.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 549.99
Price excludes VAT (USA)
  • Durable hardcover 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. NUREG-75/014. Reactor safety: An assessment of accident risk in U.S. commercial nuclear power plants, WASH-1400. U.S. Nuclear Regulatory Commission, Washington, D,. 1975.

    Google Scholar 

  2. Hauge S, Hokstad P, Langseth H. Øien K. Reliability prediction method for safety instrumented systems. PDS method handbook, edition. Report STF50 A06031, Sintef, Trondheim, Norway. 2006.

    Google Scholar 

  3. IEC 61508. Functional safety of electrical/electronic/programmable electronic safety-related systems. Parts 1–7. International Electrotechnical Commission, Geneva 1997.

    Google Scholar 

  4. Smith AM, Watson IA. Common cause failures — a dilemma in perspective. Reliability Engineering 1980; 1(2):127–142.

    Article  Google Scholar 

  5. NEA. International common-cause failure data exchange. ICDE general coding guidelines. Technical note NEA/CSNI/ R(2004)4. Nuclear Energy Agency, 2004.

    Google Scholar 

  6. NASA. Probabilistic risk assessment procedures guide for NASA managers and practitioners. NASA Office of Safety and Mission Assurance. Washington. DC, 2002.

    Google Scholar 

  7. Littlewood B. The impact of diversity upon common mode failures. Reliability Engineering and System Safety 1996; 51:101–113.

    Article  Google Scholar 

  8. Parry GW. Common cause failure analysis: A critique and some suggestions. Reliability Engineering and System Safety 1991; 34:309–320.

    Article  Google Scholar 

  9. Paula HM, Campbell DJ, Rasmuson DM. Qualitative cause-defense matrices: Engineering tools to support the analysis and prevention of common cause failures. Reliability Engineering and System Safety 1991; 34:389–415.

    Article  Google Scholar 

  10. DOE. Root cause analysis guidance document. Report no. DOE-NE-STD-1004-92. U.S. Department of Energy, Washington, DC, 1992.

    Google Scholar 

  11. Rasmuson DM. Some practical considerations in treating dependencies in PRAs. Reliability Engineering and System Safety 1991; 34:327–343.

    Article  Google Scholar 

  12. Miller AG, Kaufer B, Carlson L. Activities on component reliability under the OECD nuclear energy agency. Nuclear Engineering and Design 2000; 198:325–334.

    Article  Google Scholar 

  13. Cooper SE, Lofgren EV, Samanta PK, Wong S-M. Dependent failure analysis of NPP data bases. Nuclear Engineering and Design 1993; 142:137–153.

    Article  Google Scholar 

  14. Mosleh A, Rasmuson DM, Marshall FM. Guidelines on modeling common-cause failures in probabilistic risk assessment. U.S. Nuclear Regulatory Commission, Washington, DC, NUREG/CR-5485, 1998.

    Google Scholar 

  15. Childs JA, Mosleh A. A modified FMEA tool for use in identifying and assessing common cause failure risk in industry. Proceedings Annual Reliability and Maintainability Symposium, Washington D.C.; Jan. 18–21, 1999; 19–24.

    Google Scholar 

  16. Hauge S, Onshus T, Øien K, Grøtan TO, Holmstrøm S, Lundteigen MA. Independence of safety systems on offshore oil and gas installations 73-Status and challenges (in Norwegian). Report STF50 A06011, Sintef, Trondheim, Norway, 2006.

    Google Scholar 

  17. NASA. Fault tree handbook with aerospace applications. NASA Office of Safety and Mission Assurance, Washington. DC, 2002.

    Google Scholar 

  18. Rausand M, Høyland A. System reliability theory; models, statistical methods, and applications, 2nd edition. Wiley, New York. 2004.

    MATH  Google Scholar 

  19. Johnston BD. A structured procedure for dependent failure analysis (DFA). Reliability Engineering 1987; 19:125–136.

    Article  Google Scholar 

  20. Fleming KN. A reliability model for common mode failures in redundant safety systems. Report GA-A13284, General Atomic Company, San Diego, CA, 1975.

    Google Scholar 

  21. OREDA. Offshore reliability data, 4th ed. Available from: Det Norske Veritas, NO 1322 Høvik, Norway, 2002.

    Google Scholar 

  22. MIL-HDBK 217F. Reliability prediction of electronic equipment. U.S. Department of Defense, Washington, DC, 1991.

    Google Scholar 

  23. Evans MGK, Parry GW, Wreathall J. On the treatment of common-cause failures in system analysis. Reliability Engineering 1984; 9:107–115.

    Article  Google Scholar 

  24. Humpreys RA. Assigning a numerical value to the beta factor common cause evaluation. Reliability’ 87. Proceedings paper 2C; 1987.

    Google Scholar 

  25. Smith DJ, Simpson KGL. Functional safety — A straightforward guide to applying the IEC 61508 and related standards. Elsevier, Burlington, UK, 2005.

    Google Scholar 

  26. Brand PV. A pragmatic approach to dependent failures assessment for standard systems. AEA Technology plc.1996.

    Google Scholar 

  27. Zitrou A, Bedford T. Foundations of the UPM common cause model. In: Bedford T, Gelder PH. van, eds. Safety and Reliability. Balkema, ESREL 2003; 1769–1775.

    Google Scholar 

  28. Zitrou A, Bedford T, Walls L. Developing soft factors inputs to common cause failure models. In: Spitzer C, Schmocker U, Dang VN, eds. Probabilistic safety assessment and management. Springer, Berlin, 2004; 825–830.

    Google Scholar 

  29. Beckman LV. Match redundant system architectures with safety requirements. Chemical Engineering Progress 1995; December: 54–61.

    Google Scholar 

  30. Vesely WE. Estimating common.cause failure probabilities in reliability and risk analyses: Marshall-Olkin specializations. In: Assessment J, Fussell B, Burdick GR, eds. Nuclear systems reliability engineering and risk. SIAM, Philadelphia, 1977; 314–341.

    Google Scholar 

  31. Marshall AW, Olkin I. A multivariate exponential distribution. Journal of the American Statistical Association 1967; 62:30–44.

    Article  MATH  MathSciNet  Google Scholar 

  32. Atwood CL. The binomial failure rate commoncause model. Technometrics 1986; 28(2):139–148.

    Article  Google Scholar 

  33. Hokstad P. A shock model for common-cause failures. Reliability Engineering and System Safety 1988; 23:127–145.

    Article  Google Scholar 

  34. Apostolakis G, Moieni P. The foundations of models of dependence in probabilistic safety assessment. Reliability Engineering 1987; 18(3):177–195.

    Article  Google Scholar 

  35. Mosleh A. Common cause failures: An analysis methodology and example. Reliability Engineering and System Safety 1991; 34:249–292.

    Article  Google Scholar 

  36. Mosleh A, Siu NO. A multi-parameter common cause failure model. 9th International Conference on Structural Mechanics in Reactor Technology, Lausanne, Switzerland, Aug. 17–21, 1987; 147–152.

    Google Scholar 

  37. Mosleh A, Fleming KN, Parry GW, Paula HM, Worledge DH, Rasmuson DM. Procedures for treating common cause failures in safety and reliability studies. Analytical Background and Techniques. (EPRI NP 5613). U.S. Nuclear Regulatory Commission, Washington, DC, NUREG/CR-4780 1989; 2.

    Google Scholar 

  38. Fleming KN, Mosleh A, Deremer RK A systematic procedure for the incorporation of common cause events into risk and reliability models. Nuclear Engineering and Design 1985; 93:245–279.

    Article  Google Scholar 

  39. Hokstad P, Corneliussen K. Loss of safety assessment and the IEC 61508 standard. Reliability Engineering and System Safety 2004; 83:111–120.

    Article  Google Scholar 

  40. Hokstad P. Common cause and dependent failure modeling. In: Misra KB, editor. New Trends in system reliability evaluation. Chapter 11, Elsevier, Amsterdam, 1993; 411–444.

    Google Scholar 

  41. ICDE. International Common Cause Failure Data Exchange Project. http://www.nea.fr/html/jointproj/icde.html

    Google Scholar 

  42. Baranowsky P, Rasmuson D, Johanson G, Kreuser A, Pyy P, Werner W. General insights from the international common cause failure data exchange (ICDE) project. In Proceedings PSAM 7 ESREL Berlin; June 14–18, 2004:70–75.

    Google Scholar 

  43. Tirira J, Werner W. Lessons learnt from data collected in the ICDE project. In Proceedings PSAM 7, ESREL, Berlin; June 14–18, 2004:82–87.

    Google Scholar 

  44. Johanson G, Jonsson E, Jãnkãlã K, Pesonen J, and Werner W. Insights and results from the analyses of common-cause failure data collected in the ICDE Project for Safety and Relief Valves. In Proceedings PSAM 7, ESREL, Berlin; June 14–18, 2004: 88–93.

    Google Scholar 

  45. SKI, CCF analysis of high redundancy systems, safety/relief valve data analysis and reference BWR application. SKI Technical Report 91:6, Stockholm. http://www.ski.se/extra/document/?instance=1&action_show_document.122.=1 1992.

    Google Scholar 

  46. SKI, Analysis of CCF for hydraulic scram and control rod systems in BWRs. http://www.ski.se/dynamaster/file_archive/030117/f6fefeb66a3209faccd6387d4f804bf2/96%2d77.pdf 1996.

    Google Scholar 

  47. SKI, Investigates events that (potentially) lead to CCF. SKI Technical Report 98:09. http://www.ski.se/dynamaster/file_archive/010803/97837624857/98%2d9.pdf; 1998.

    Google Scholar 

  48. Hokstad P, Maria A, Tomis P. Estimation of common cause factors from systems with different numbers of channels. IEEE Transactions on Reliability 2006; 55(1):18–25.

    Article  Google Scholar 

  49. Knochenhauer M, Mankamo T, Pörn K. Analysis and modelling of dependent failures. In Proceedings from PSAM 7, ESREL, Berlin; June 14–18, 2004; 831–836.

    Google Scholar 

  50. Xie L. A knowledge-based multi-dimension discrete common cause failure model. Nuclear Engineering and Design 1998; 183:107–116.

    Article  Google Scholar 

  51. Kvam PH, Miller JG. Common cause failure prediction using data mapping. Reliability Engineering and System Safety 2002; 76:273–278.

    Article  Google Scholar 

  52. Vaurio JK. Consistent mapping of common cause failure rates and alpha factors. Reliability Engineering and System Safety 2007; 92:628–645.

    Article  Google Scholar 

  53. Mosleh A, Fleming KN, Parry GW, Paula HM, Worledge DH, Rasmuson DM. Procedures for treating common cause failures in safety and reliability studies. Procedural framework and examples. (EPRI NP 5613). U.S. Nuclear Regulatory Commission, Washington, DC, NUREG/CR-4780 1988; 1.

    Google Scholar 

  54. Massieu A, Xingquan W. Fuzzy parametrization of Bulgaria’s nuclear policy decision. Journal of Performability Engineering 2005; 1(2):167–178.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag London Limited

About this chapter

Cite this chapter

Hokstad, P., Rausand, M. (2008). Common Cause Failure Modeling: Status and Trends. In: Misra, K.B. (eds) Handbook of Performability Engineering. Springer, London. https://doi.org/10.1007/978-1-84800-131-2_39

Download citation

  • DOI: https://doi.org/10.1007/978-1-84800-131-2_39

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84800-130-5

  • Online ISBN: 978-1-84800-131-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics