Skip to main content
Log in

Reliability modeling and evaluation of uncertain random cold standby k-out-of-m + n: G systems

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

Based on the uncertainty of the system working environment, this paper models and evaluates reliability for uncertain random cold standby k-out-of-m + n: G systems with uncertain parameters. Assume that the system is composed of m + n subsystems. The lifetime distributions of components in m subsystems obey probability distributions with uncertain parameters, and the lifetime distributions of components in n subsystems obey uncertainty distributions with uncertain parameters. The parameters of all the lifetime distributions are uncertain variables and obey the uncertainty distributions. Under the assumption that the switch is completely reliable, three types of reliability models for cold standby systems with uncertain parameters, including the random cold standby k-out-of-m: G system model, the uncertain cold standby k-out-of-n: G system model, and the uncertain random cold standby k-out-of-m + n: G system model are developed. The reliability functions and mean time to failure of these system models are evaluated by probability theory and uncertainty theory. Numerical examples are presented to illustrate the modeling and evaluation methods of the proposed models. The system reliability model with uncertain parameters is also compared with that with constant parameters in the examples provided. The comparison results show the usability and superiority of the reliability models developed in this paper.

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
Fig. 4
Fig. 5

Similar content being viewed by others

Data availability

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

References

  • Behboudi Z, Borzadaran GM, Asadi M (2021) Reliability modeling of two-unit cold standby systems: a periodic switching approach. Appl Math Model 92:179–195

    Article  MathSciNet  MATH  Google Scholar 

  • Cao XR, Hu LM, Li ZZ (2019) Reliability analysis of discrete time series-parallel systems with uncertain parameters. J Amb Intell Hum Comput 10(9):2657–2668

    Article  Google Scholar 

  • Cekyay B (2020) Reliability of mission-based k-out-of-n systems with exponential phase durations and component lifetimes. Proc Inst Mech Eng O-J Ris Reliab 235(3):446–457

    Google Scholar 

  • Chen X, Zhu YG (2021) Optimal control for uncertain random singular systems with multiple time-delays. Chaos Solitons Fractals 152:111371

    Article  MathSciNet  MATH  Google Scholar 

  • Dembinska A, Nikolov NI, Stoimenova E (2021) Reliability properties of k-out-of-n systems with one cold standby unit. J Comput Appl Math 388:113289

    Article  MathSciNet  MATH  Google Scholar 

  • Eryilmaz S, Devrim Y (2019) Reliability and optimal replacement policy for a k-out-of-n system subject to shocks. Reliab Eng Syst Saf 188:393–397

    Article  Google Scholar 

  • Eryilmaz S, Erkan TE (2018) Coherent system with standby components. Appl Stoch Model Bus 34(3):395–406

    Article  MathSciNet  MATH  Google Scholar 

  • Gao R, Ahmadzade H (2021) Convergence in distribution for uncertain random sequences with dependent random variables. J Syst Sci Comput 34(2):483–501

    MathSciNet  MATH  Google Scholar 

  • Gao Y, Gao R, Yang LX (2015) Analysis of order statistics of uncertain variables. J Uncertain Anal Appl 3(1):1–7

    Article  Google Scholar 

  • Gao R, Sun Y, Ralescu DA (2016) Order statistics of uncertain random variables with application to k-out-of-n system. Fuzzy Optim Decis Mak 16(2):159–181

    Article  MathSciNet  MATH  Google Scholar 

  • Gao JW, Yao K, Zhou J et al (2018) Reliability analysis of uncertain weighted k-out-of-n systems. IEEE Trans Fuzzy Syst 26(5):2663–2671

    Article  Google Scholar 

  • Hu LM, Cao XR, Li ZZ (2019) Reliability analysis of discrete time redundant system with imperfect switch and random uncertain lifetimes. J Intell Fuzzy Syst 397(1):23–35

    Google Scholar 

  • Hu LH, Kang R, Pan X et al (2020) Uncertainty expression and propagation in the risk assessment of uncertain random system. IEEE Syst J 15(2):1604–1615

    Article  Google Scholar 

  • Huang XX, Jiang GW (2021) Portfolio management with background risk under uncertain mean–variance utility. Fuzzy Optim Decis Mak 20:315–330

    Article  MathSciNet  MATH  Google Scholar 

  • Huang M, Ren L, Lee LH et al (2016) Model and algorithm for 4plrp with uncertain delivery time. Inform Sci 330(10):211–225

    Article  Google Scholar 

  • Jasinski K (2021) Some conditional reliability properties of k-out-of-n system composed of different types of components with discrete independent lifetimes. Metrika. https://doi.org/10.1007/S00184-021-00826-1

    Article  MathSciNet  MATH  Google Scholar 

  • Jin T, Gao S, Xia H et al (2021) Reliability analysis for the fractional-order circuit system subject to the uncertain random fractional-order model with caputo type. J Adv Res 32:15–26

    Article  Google Scholar 

  • Li B, Sun YF, Teo KL (2021) An analytic solution for multi-period uncertain portfolio selection problem. Fuzzy Optim Decis Mak. https://doi.org/10.1007/s10700-021-09367-8

    Article  MATH  Google Scholar 

  • Liu BD (2007) Uncertainty theory, 2nd edn. Springer, Berlin

    MATH  Google Scholar 

  • Liu BD (2010a) Uncertain risk analysis and uncertain reliability analysis. J Uncertain Syst 4(3):163–170

    Google Scholar 

  • Liu BD (2010b) Uncertainty theory: a branch of mathematics for modeling human uncertainty. Springer, Berlin

    Book  Google Scholar 

  • Liu W (2013a) Reliability analysis of redundant system with uncertain lifetimes. Int Inf Ins Inf 16(2):881–888

    Google Scholar 

  • Liu YH (2013b) Uncertain random variables: a mixture of uncertainty and randomness. Soft Comput 17(4):625–634

    Article  MATH  Google Scholar 

  • Liu BD (2015) Uncertainty theory, 4th edn. Springer, Berlin

    Book  MATH  Google Scholar 

  • Liu YH, Ha MH (2010) Expected value of function of uncertain variables. J Uncertain Syst 4(3):181–186

    Google Scholar 

  • Liu YH, Ralescu DA (2017) Value-at-risk in uncertain random risk analysis. Inform Sci 391:1–8

    MathSciNet  MATH  Google Scholar 

  • Liu BL, Zhang ZQ, Wen YQ (2019a) Reliability analysis for devices subject to competing failure processes based on chance theory. Appl Math Model 75:398–413

    Article  MathSciNet  MATH  Google Scholar 

  • Liu Y, Qu ZQ, Li XZ et al (2019b) Reliability modelling for repairable systems with stochastic lifetimes and uncertain repair times. IEEE Trans Fuzzy Syst 27(12):2396–2405

    Article  Google Scholar 

  • Liu ZC, Hu LM, LS J (2019c) Reliability analysis of general systems with bi-uncertain variables. Soft Comput 24:6975–6986

    Article  MATH  Google Scholar 

  • Liu YJ, Ahmadzade H, Farahikia M (2021) Portfolio selection of uncertain random returns based on value at risk. Soft Comput 25(8):6339–6346

    Article  MATH  Google Scholar 

  • Sheng YH, Ke H (2020) Reliability evaluation of uncertain k-out-of-n systems with multiple states. Reliab Eng Syst Saf 195:106696

    Article  Google Scholar 

  • Van G, Arjan JC, Reijns GL (2012) Reliability analysis of k-out-of-n systems with single cold standby using pearson distributions. IEEE Trans Reliab 61(2):526–532

    Article  Google Scholar 

  • Wang X, Ning YF (2018) Uncertain chance-constrained programming model for project scheduling problem. J Oper Res Soc 69(3):384–391

    Article  Google Scholar 

  • Wang XS, Li XN, Wang JW (2018) Urban water conservation evaluation based on multi-grade uncertain comprehensive evaluation method. Water Resour Manag 32(2):417–431

    Article  Google Scholar 

  • Wen ML, Kang R (2016) Reliability analysis in uncertain random system. Fuzzy Optim Decis Mak 15(4):491–506

    Article  MathSciNet  MATH  Google Scholar 

  • Wu QT (2012) Reliability analysis of a cold standby system attacked by shocks. Appl Math Comput 218(23):11654–11673

    MathSciNet  MATH  Google Scholar 

  • Xu QQ, Zhu YG (2020) Uncertain random optimization models based on system reliability. Int J Comput Int Syst 13(1):1498–1506

    Article  Google Scholar 

  • Yang M, Ni YD, Liu Y (2021a) A multi-objective consistent home healthcare routing and scheduling problem in an uncertain environment. Comput Ind Eng. https://doi.org/10.1016/j.cie.2021.107560

    Article  Google Scholar 

  • Yang Y, Huang SY, Wen ML, Chen X, Zhang QY, Liu W (2021b) Analyzing travel time belief reliability in road network under uncertain random environment. Soft Comput 25(15):10053–10065

    Article  Google Scholar 

  • Yao K, Gao JW (2015) Uncertain random alternating renewal process with application to interval availability. IEEE Trans Fuzzy Syst 23(5):1333–1342

    Article  Google Scholar 

  • Zhang QY, Kang R, Wen ML (2018) Belief reliability for uncertain random systems. IEEE Trans Fuzzy Syst 26(6):3605–3614

    Article  Google Scholar 

  • Zhang QY, Kang R, Wen ML (2019) Decomposition method for belief reliability analysis of complex uncertain random systems. IEEE Trans Fuzzy Syst 7:132711–132719

    Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 72071175) and the Project of Hebei Key Laboratory of Software Engineering (No. 22567637H).

Author information

Authors and Affiliations

Authors

Contributions

All authors contributed to the study conception and design. Funding acquisition and conceptualization were performed by Linmin Hu. Writing-review and editing were performed by Xiangfeng Yang and Mingjia Li. The first draft of the manuscript was written by Zhuoxin Bai. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Linmin Hu.

Ethics declarations

Conflict of interest

The authors have no conflicts or competing interests to declare.

Additional information

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

Hu, L., Bai, Z., Yang, X. et al. Reliability modeling and evaluation of uncertain random cold standby k-out-of-m + n: G systems. J Ambient Intell Human Comput 14, 13833–13846 (2023). https://doi.org/10.1007/s12652-022-04075-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-022-04075-6

Keywords

Navigation