Skip to main content
Log in

Time-dependent intuitionistic fuzzy system reliability analysis

  • Methodologies and Application
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

The purpose of the present paper is to provide a method for constructing time-dependent reliability systems based on intuitionistic fuzzy random variables. A lifetime variable cannot be precisely recorded due to machine errors, experimentation pitfalls, personal judgments, estimation errors or other unexpected sources of error. In order to satisfy the purpose of this paper, an intuitionistic fuzzy random variable with exact parameters was introduced and adopted to evaluate the reliability functions of a k-out-of-n system, with some reliability evaluation criteria discussed and interpreted. Numerical evaluations were further presented to illustrate the calculation of the system reliability criteria in the form of intuitionistic fuzzy numbers. Finally, a number of potential engineering applications of the proposed method were presented.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Aliev IM, Kara Z (2004) Fuzzy system reliability analysis using time dependent fuzzy set. Control Cybern 33:653–662

    MathSciNet  MATH  Google Scholar 

  • Atanassov K (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20:87–96

    Article  Google Scholar 

  • Atanassov K (1994) New operations defined over the intuitionistic fuzzy sets. Fuzzy Sets Syst 61:137–142

    Article  MathSciNet  Google Scholar 

  • Baraldi P, Podofillini L, Mkrtchyan L, Zio E, Dang VN (2015) Comparing the treatment of uncertainty in Bayesian networks and fuzzy expert systems used for a human reliability analysis application. Reliab Eng Syst Saf 138:176–193

    Article  Google Scholar 

  • Chaube S, Singh SB (2016) Fuzzy reliability of two-stage weighted-k-out-of-n systems with common components. Int J Math Eng Manag Sci 1:41–51

    Google Scholar 

  • Dong YG, Chen XZ, Cho HD, Kwon JW (2003) Simulation of fuzzy reliability indexes. J Mech Sci Technol 17:492–500

    Google Scholar 

  • Hafaifa A, Laaouad F, Guemana M (2009) A new engineering method for fuzzy reliability analysis of surge control in centrifugal compressor. Am J Eng Appl Sci 2:676–682

    Article  Google Scholar 

  • He Q, Yabing ZHA, Zhang R, Sun Q, Liu T (2017) Reliability analysis for multi-state system based on triangular fuzzy variety subset bayesian networks. Eksploat Niezawodn Maint Reliab 19:152–165

    Article  Google Scholar 

  • Hussian MA, Amin EA (2017) Fuzzy reliability estimation for exponential distribution using ranked set sampling. Int J Contemp Math Sci 12:31–42

    Article  Google Scholar 

  • Jamali S, Bani MJ (2017) Application of fuzzy assessing for reliability decision making. arXiv preprint arXiv:1707.01727

  • Jamkhaneh EB (2011) An evaluation of the systems reliability using fuzzy lifetime distribution. J Appl Math Islamic Azad Univ Lahijan 7:73–80

    Google Scholar 

  • Kumar G, Bajaj RK (2014) Intuitionistic fuzzy reliability of K-out-of-N: G system using statistical confidence interval. Int J Appl Inf Syst 7:1–7

    Google Scholar 

  • Kumar M, Yadav SP (2012) A novel approach for analyzing fuzzy system reliability using different types of intuitionistic fuzzy failure rates of components. ISA Trans 51:288–297

    Article  Google Scholar 

  • Kumar A, Yadav SP, Kumar S (2007) New approach for electric robot fuzzy reliability analysis. Int J Perform Eng 3:257–266

    Google Scholar 

  • Kumar M, Yadav SP, Kumar S (2013) Fuzzy system reliability evaluation using time-dependent intuitionistic fuzzy set. Int J Syst Sci 44:50–66

    Article  MathSciNet  Google Scholar 

  • Kwakernaak H (1978) Fuzzy random variables, part I: definitions and theorems. Inf Sci 19:1–15

    Article  Google Scholar 

  • Lee KH (2005) First course on fuzzy theory and applications. Springer, Berlin

    MATH  Google Scholar 

  • Lee HM, Fuh CF, Su JS (2012) Fuzzy parallel system reliability analysis based on level \((\lambda, \rho )\) interval-valued fuzzy numbers. Int J Innov Comput Inf Control 8:5703–5713

    Google Scholar 

  • Liu S, Zhang H, Li C, Lu H, Hu Y (2014) Fuzzy reliability estimation for cutting tools. Procedia CIRP 15:62–67

    Article  Google Scholar 

  • Mahapatra GS, Roy TK (2012) Reliability evaluation of complex system with fuzzy reliability of components using interval nonlinear programming. Electron J Appl Stat Anal 5:151–163

    MathSciNet  Google Scholar 

  • Panda DC (2016) A new method for evaluation of fuzzy reliability of multistage interconnection. Int J Res Appl Sci 3:14–20

    Google Scholar 

  • Rao KD, Kushwaha HS, Verma AK, Srividya A (2009) A new uncertainty importance measure in fuzzy reliability analysis. Int J Perform Eng 5:219–226

    Google Scholar 

  • Razak KA, Rajakumar K (2013) A study on fuzzy reliability measures. Appl Math Sci 7:3335–3343

    MathSciNet  Google Scholar 

  • Sharma MK (2017) Possibility and probability aspect to fuzzy reliability analysis of a network system. Global J Pure Appl Math 13:3641–3655

    Article  Google Scholar 

  • Tang Z, Lu Z, Xia Y (2013) Numerical method for fuzzy reliability analysis. J Aircr 50:1710–1715

    Article  Google Scholar 

  • Tao YR, Cao L, Huang ZH (2017) A novel evidence-based fuzzy reliability analysis method for structures. Struct Multidiscip Optim 55:1237–1249

    Article  MathSciNet  Google Scholar 

  • Wu HC (2004) Fuzzy reliability estimation using Bayesian approach. Comput Ind Eng 46:467–493

    Article  Google Scholar 

  • Xu X, Mitra J (2010) Distribution system reliability evaluation using credibility theory. Int J Eng Sci Technol 2:107–118

    Article  Google Scholar 

  • Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the editor and anonymous reviewers for their constructive suggestions and comments, which improved the presentation of this work.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gholamreza Hesamian.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by the authors.

Additional information

Communicated by V. Loia.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Akbari, M.G., Hesamian, G. Time-dependent intuitionistic fuzzy system reliability analysis. Soft Comput 24, 14441–14448 (2020). https://doi.org/10.1007/s00500-020-04796-w

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-020-04796-w

Keywords

Navigation