Journal of Failure Analysis and Prevention

, Volume 11, Issue 1, pp 56–70 | Cite as

Reliability Assessment of Cogeneration Power Plant in Textile Mill Using Fault Tree Analysis

  • Vallem Ramesh
  • R. Saravannan
Technical Article---Peer-Reviewed


The Combined Heat and Power (CHP) Systems are systems that simultaneously generate both electricity and useful heat. It is important to analyze the reliability of these systems to ensure the lowest level of life cycle cost. A CHP system installed in a textile mill is considered as a case study to assess the reliability through fault tree analysis (FTA). The common cause failures (CCFs) are evaluated using the β-factor model with the available data on the failure of the plant. On a detailed analysis, it is found that the unavailability of the plant is 8.50E−03, which is predominantly caused by the problems related to mechanical system, subsystems of boiler, and turbine. The repair and the restoration times for these components used in the fault tree analysis (FTA) are 48 and 8 h, respectively. Hence, faster restoration of these components affected by shutdown/failure and implementation of reliability-centered maintenance (RCM) features will significantly improve the reliability of the system, thereby reducing the time with respect to return on the investment.


Fault tree analysis Common cause failures Minimal cut set 



Failure rate


Parametric factor


Component having two modes, i.e., working or failed


Component failure rate


Component repair rate


Mean failure rate of a component, h−1




Mean unavailability of a component [Q-Factor = (1 − Availability)]


Demand failure probability


Time taken to repair a component, h


Mean time between failures


Mean time to repair


Common cause failure


Minimum cut set


Testing Frequency


Time to first failure, h


Basic events


Vacuum circuit breaker


Mega volt ampere


Combined heat and power


Fault tree analysis


Reliability-centered maintenance


Preventive maintenance


  1. 1.
    Mazur, V.: Fuzzy thermo economic optimization of energy-transforming systems. Appl. Energy 84, 749–762 (2007)CrossRefGoogle Scholar
  2. 2.
    De Paepe, M., Mertens, D.: Combined heat and power in a liberalised energy market. Energy Convers. Manag. 48, 2542–2555 (2007)CrossRefGoogle Scholar
  3. 3.
    Cai, Y.P., Huang, G.H., Yang, Z.F., Tan, Q.: Identification of optimal strategies for energy management systems planning under multiple uncertainties. Appl. Energy 86, 480–495 (2009)CrossRefGoogle Scholar
  4. 4.
    Zio, E.: Reliability engineering: old problems and new challenges. Reliab. Eng. Syst. Saf. 94(2), 125–141 (2009)CrossRefGoogle Scholar
  5. 5.
    Eti, M.C., Ogaji, S.O.T., Probert, S.D.: Reliability of the Afam Electric Power Generating Station, Nigeria. Appl. Energy 77(3), 309–315 (2004)CrossRefGoogle Scholar
  6. 6.
    Vesely, W.E., Dugan, J., Fragola, J., Minarick, J., Railsback, J.: Fault Tree Handbook with Aerospace Applications. National Aeronautics and Space Administration, NASA (2002)Google Scholar
  7. 7.
    Volkanovski, A., Čepin, M., Mavko, B.: Application of the fault tree analysis for assessment of power system reliability. Reliab. Eng. Syst. Saf. 94(6), 1116–1127 (2009)CrossRefGoogle Scholar
  8. 8.
    Shalev, D.M., Tiran, J.: Condition-based fault tree analysis (CBFTA): a new method for improved fault tree analysis (FTA). Reliab. Eng. Syst. Saf. 92, 1231–1241 (2007)CrossRefGoogle Scholar
  9. 9.
    Dutuit, Y., Rauzy, A.: Approximate estimation of system reliability via fault trees. Reliab. Eng. Syst. Saf. 87(2), 163–172 (2005)CrossRefGoogle Scholar
  10. 10.
    Churchley, A.R.: A rationale for the reliability assessment of high integrity mechanical systems. Reliab. Eng. 19, 59–71 (1987)CrossRefGoogle Scholar
  11. 11.
    Giaccone, L., Canova, A.: Economical comparison of CHP systems for industrial user with large steam demand. Appl. Energy 86, 904–914 (2009)CrossRefGoogle Scholar
  12. 12.
    Ramirez-Marqueza, J.E., Coit, D.W.: Optimization of system reliability in the presence of common cause failures. Reliab. Eng. Syst. Saf. 92, 1421–1434 (2007)CrossRefGoogle Scholar
  13. 13.
    Senthil Kumar, C., John Arul, A., Singh, O.P., Suryaprakasa Rao, K.: Reliability analysis of shutdown system. Ann. Nucl. Energy 32, 63–87 (2005)CrossRefGoogle Scholar
  14. 14.
    Howard, R., Cooper, D.J.: Performance assessment of non-self-regulating controllers in a cogeneration power plant. Appl. Energy 86, 2121–2129 (2009)CrossRefGoogle Scholar
  15. 15.
    Eti, M.C., Ogaji, S.O.T., Probert, S.D.: Integrating reliability, availability, maintainability and supportability with risk analysis for improved operation of the Afam thermal power-station. Appl. Energy 84(2), 202–221 (2007)CrossRefGoogle Scholar
  16. 16.
    Thorin, E., Brand, H., Weber, C.: Long-term optimization of cogeneration systems in a competitive market environment. Appl. Energy 81(2), 152–169 (2005)CrossRefGoogle Scholar
  17. 17.
    Arifujjaman, Md., Iqbal, M.T., Quaicoe, J.E.: Reliability analysis of grid connected small wind turbine power electronics. Appl. Energy 86, 1617–1623 (2009)CrossRefGoogle Scholar
  18. 18.
    IAEA-TECDOC-648: Procedures for Conducting Common Cause Failure Analysis in Probabilistic Safety Assessment. International Atomic Energy Agency (1992)Google Scholar
  19. 19.
    Kvam, P.H.: A parametric mixture—model for common-cause failure data. IEEE Trans. Reliab. 47(1), 30–34 (1998)CrossRefGoogle Scholar
  20. 20.
    Choi, J.S., Cho, N.Z.: A practical method for accurate quantification of large fault trees. Reliab. Eng. Syst. Saf. 92(7), 971–982 (2007)CrossRefGoogle Scholar
  21. 21.
    RiskSpectrum® FTA advanced fault tree software toolGoogle Scholar
  22. 22.
    Rausand, M.: Reliability centered maintenance. Reliab. Eng. Syst. Saf. 60, 121–132 (1998)CrossRefGoogle Scholar
  23. 23.
    Chenga, Z., Jiab, X., Gao, P., Wua, S., Wanga, J.: A framework for intelligent reliability centered maintenance analysis. Reliab. Eng. Syst. Saf. 93, 784–792 (2008)Google Scholar

Copyright information

© ASM International 2010

Authors and Affiliations

  1. 1.Refrigeration and Air Conditioning Laboratory, Department of Mechanical EngineeringAnna UniversityChennaiIndia

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