Fuzzy Bayesian Estimation of Linear (Circular) Consecutive k-out-of-n: F System Reliability
DOI:
https://doi.org/10.48048/tis.2022.2706Keywords:
Fuzzy Bayesian reliability, Consecutive k-out-of-n:F system, Squared error loss function, Gamma distribution, Confidence intervalAbstract
The consecutive k-out-of-n: F structure is broadly applicable in industrial and military frameworks. Without lifetime information about the entire design, it is appealing to use fuzzy earlier beliefs on its segments. In this paper the fuzzy Bayesian reliability assessment of the linear (circular) consecutive k-out-of-n: F system is proposed under the squared error loss function. The parameters are known as fuzzy random variables in the process of obtaining fuzzy Bayesian reliability. The conventional strategy for estimating Bayesian reliability will be utilized to construct the fuzzy Bayesian point estimator of the proposed system by applying the Resolution Identity theorem. A comparative study of the derived result with the literature is presented.
HIGHLIGHTS
- Reliability Estimate of Consecutive k-out-of-n: F system
- Parameters are known as fuzzy random variables
- Applied Resolution Identity Theorem to estimate fuzzy Bayesian reliability
- Fuzzy Bayesian system reliability is calculated
- Fuzzy mean time to failure is calculated
GRAPHICAL ABSTRACT
Downloads
Metrics
References
LA Zadeh. Fuzzy sets. information and control. 1965;8, p. 338-53.
LA Zadeh. Probability measures of fuzzy events. J. Math. Anal. 1968; 23, 421-7.
LV Utkin. Knowledge based fuzzy reliability assessment. Microelectron. Reliab. 1994; 34, 863-74.
ML Puri and D Ralescu. Fuzzy random variables. J. Math. Anal. 1986; 114, 409-22.
RG Almond. Discussion: Fuzzy logic: Better science? Or better engineering? Amer. Stat. Assoc. Amer. Soc. Qual. Control. 1995; 37, pp.267-270.
EA Pekoz and SM Ross. A simple derivation of exact reliability formulas for linear and circular consecutive-k-of-n: F system. J. Appl. Prob. 1995; 32, 554-7.
M Lambiris and S Papastavridis. Exact reliability formulas for linear and circular consecutive-k-out-of-n: F ststems. IEEE Trans. Reliab. 1985; 34, 124-6.
B Rezaeianjouybari, M Sheikholeslami, A Shafee and H Babazadeh. A novel Bayesian optimization for flow condensation enhancement using nanorefrigerant: A combined analytical and experimental study. Chem. Eng. Sci. 2019; 215, 1-9.
M Sheikholeslami, SA Farshad, Z Ebrahimpour and Z Said. Recent progress on flat plate solar collectors and photovoltaic systems in the presence of nanofluid: A review. J. Clean. Prod. 2021; 293, 119-26.
M Sheikholeslami and SA Farshad. Investigation of solar collctor system with turbulator considering hybrid nanoparticles. Renew. Energ. 2021; 171, 1128-58.
CH Cheng. Fuzzy consecutive-k-out-of-n:F system reliability. Microelectron. Reliab. 1994; 34, 1909-22.
EM Elghamry, MA Eldamcesse and MS Nayel. Reliability model of fuzzy consecutive-k-out-of-n: F system. Int. J. Reliab. Risk Saf. Theory Appl. 2019; 2, 1-4.
KK Sharma and H Krishna. Bayesian reliability analysis of a k-out-of-m system and the estimation of sample size and censoring time. Reliab. Eng. Syst. Saf. 1994; 44, 11-15.
J Madhumitha and G Vijayalakshmi. Bayesian estimation of linear (Circular) consecutive k-out-of-n: F system reliability. Int. J. Perform. Eng. 2020; 10, 1509-16.
KC Chou and J Yuan. Fuzzy Bayesian approach to reliability of existing structures. J. Struct. Eng. 1993; 119, 3276-90.
S Tavassoli, FS Taha-Hossein Hejazi. A fuzzy approach to reliability analysis. J. Ind. Eng. Manag. 2017; 4, 55-68.
ZG Li, JG Zhou and BY Liu. System reliability analysis method based on fuzzy probability. Int. J. Fuzzy Syst. 2017; 19, 1759-67.
HC Wu. The fuzzy estimators of fuzzy parameters based on fuzzy random variables. Eur. J. Oper. Res. 2003; 146, 101-14.
Hsien-Chung Wu. Fuzzy Bayesian system reliability assessment based on exponential distribution. Appl. Math. Model. 2006; 30, 509-30.
L Gorkemli and S Ulusoy. Fuzzy bayesian reliability and availability analysis of production system. Comput. Ind. Eng. 2010; 59, 690-6.
R Gholizadeh, A Mastanishirazi and BS Gildeh. Fuzzy Bayesian system reliability assessment based on prior two-parameter exponential distribution under different loss function. Softw. Test. Verification Reliab. 2012; 22, 203-17.
S Kabir and Y Papadopoulos. A review of applications of fuzzy sets to safety and reliability engineering. Int. J. Approx. Reason. 2018; 100, 29-55.
W kuo, MJ Zuo. Optimal Reliability Modeling Principles and Applications. John Wiley & Sons, Hoboken, New Jersey, 2003.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
