Fuzzy Reliability Analysis of Washing Unit in a Paper Plant Using Soft-Computing Based Hybridized Techniques

  • Komal
  • S. P. Sharma
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 223)


The present study deals with the fuzzy reliability analysis of washing unit in a paper plant utilizing available uncertain data which reflects their components’ failure and repair pattern. Paper computes different reliability parameters of the system in the form of fuzzy membership functions. Two soft-computing based hybridized techniques namely Genetic Algorithms Based Lambda-Tau (GABLT) and Neural Network and Genetic Algorithms Based Lambda-Tau (NGABLT) along with traditional Fuzzy Lambda-Tau (FLT) technique are used to evaluate the fuzzy reliability parameters of the system. In FLT, ordinary fuzzy arithmetic is utilized while in GABLT and NGABLT ordinary arithmetic and nonlinear programming approach are used. The computed results, as obtained by these techniques, are compared. Crisp and defuzzified results are also computed. Based on results some important suggestions are given for future course of action in maintenance planning.


  1. 1.
    Komal, Sharma, S.P., Kumar, D.: RAM analysis of repairable industrial systems utilizing uncertain data. Appl. Soft Comput. 10(4), 1208–1221 (2010)CrossRefGoogle Scholar
  2. 2.
    Sharma, S.P., Kumar, D., Komal, : Stochastic behavior analysis of the feeding system in a paper mill using NGABLT technique. Int. J. Qual. Reliab. Manage. 27(8), 953–971 (2010)Google Scholar
  3. 3.
    Knezevic, J., Odoom, E.R.: Reliability modeling of repairable systems using Petri nets and Fuzzy Lambda-Tau Methodology. Reliab. Eng. Syst. Saf. 73(1), 1–17 (2001)CrossRefGoogle Scholar
  4. 4.
    Huang, H.Z., Zuo, M.J., Sun, Z.Q.: Bayesian reliability analysis for fuzzy lifetime data. Fuzzy Sets Syst. 157(12), 1674–1686 (2006)MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    Sharma, R.K.: Analysis, design and optimization of QRM aspects in production systems. Indian Institute of Technology Roorkee, Roorkee, Uttrakhand, India (2006)Google Scholar
  6. 6.
    Rao, K.D., Kushwaha, H.S., Verma, A.K., Srividya, A.: Quantification of epistemic and aleatory uncertainties in level-1 probabilistic safety assessment studies. Reliab. Eng. Syst. Saf. 92(7), 947–956 (2007)CrossRefGoogle Scholar
  7. 7.
    Kumar, D.: Analysis and optimization of systems availability in sugar, paper and fertilizer Industries. University of Roorkee (Presently IIT Roorkee), Uttrakhand. India (1991)Google Scholar
  8. 8.
    Chen, S.M.: Fuzzy system reliability analysis using fuzzy number arithmetic operations. Fuzzy Sets Syst. 64(1), 31–38 (1994)CrossRefGoogle Scholar
  9. 9.
    Pedrycz, W.: Why triangular membership functions? Fuzzy Sets Syst. 64(1), 21–30 (1994)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Tillman, F.A., Hwang, C.L., Kuo, W.: Optimization of Systems Reliability. Marcel Dekker, New York (1980)zbMATHGoogle Scholar
  11. 11.
    Konak, A., Coit, D.W., Smith, A.: Multi-objective optimization using genetic algorithms: a tutorial. Reliab. Eng. Syst. Saf. 91(9), 992–1007 (2006)CrossRefGoogle Scholar
  12. 12.
    Goldberg, D.E.: Genetic Algorithm in Search, Optimization and Machine Learning. Addison-Wesley, Boston (1989)Google Scholar
  13. 13.
    Cybenko, G.: Approximation by superpositions of a sigmoidal function. Reliab. Eng. Syst. 2(4), 303–314 (1989)MathSciNetzbMATHGoogle Scholar
  14. 14.
    Kosko, B.: Neural Networks and Fuzzy System: A Dynamical Systems Approach to Machine Intelligence. Prentice-Hall, Englewood (1991)Google Scholar
  15. 15.
    Ross, T.J.: Fuzzy Logic with Engineering Applications, 2nd edn. Wiley, New York (2004)zbMATHGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of MathematicsUniversity of Petroleum and Energy Studies (UPES)DehradunIndia
  2. 2.Department of MathematicsIndian Institute of Technology Roorkee (IITR)RoorkeeIndia

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