Reliability estimation of a consecutive k-out-of-n system for non-identical strength components with applications to wind speed data

References

• Ahmadi, K., & Ghafouri, S. (2019). Reliability estimation in a multicomponent stress-strength model under generalized half-normal distribution based on progressive type-II censoring. Journal of Statistical Computation and Simulation, 89(13), 2505–2548. https://doi.org/10.1080/00949655.2019.1624750
   Web of Science ®Google Scholar
• Akgül, F. G., & Şenoğlu, B. (2017). Estimation of P(X<Y)) using ranked set sampling for the Weibull distribution. Quality Technology & Quantitative Management, 14(3), 296–309. https://doi.org/10.1080/16843703.2016.1226590
   Web of Science ®Google Scholar
• Akgül, F. G., & Şenoğlu, B. (2019). Comparison of wind speed distributions: A case study for Aegean coast of Turkey. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. https://doi.org/10.1080/15567036.2019.1663309
   Web of Science ®Google Scholar
• Akici, F. (2010). Reliability analysis of consecutive k systems in a stress-strength setup. M.Sc. Thesis, Graduate School of Natural and Applied Sciences.
   Google Scholar
• Asadi, S., & Panahi, H. (2022). Estimation of stress-strength reliability based on censored data and its evaluation for coating processes. Quality Technology & Quantitative Management, 19(3), 379–401. https://doi.org/10.1080/16843703.2021.2001129
   Web of Science ®Google Scholar
• Bhattacharyya, G. K., & Johnson, R. A. (1974). Estimation of reliability in a multicomponent stress-strength model. Journal of the American Statistical Association, 69(348), 966–970. https://doi.org/10.1080/01621459.1974.10480238
   Web of Science ®Google Scholar
• Birnbaum, Z. W. (1956). On a use of Mann-Whitney statistics. In Proceedings of the third Berkeley symposium on mathematical statistics and probability (Vol. 1, pp. 13–17). Berkeley, CA, USA: University of California Press.
   Google Scholar
• Byrd, R. H., Lu, P., Nocedal, J., & Zhu, C. (1995). A limited memory algorithm for bound constrained optimization. SIAM Journal on Scientific Computing, 16(5), 1190–1208. https://doi.org/10.1137/0916069
   Web of Science ®Google Scholar
• Çetinkaya, Ç. (2021a). Reliability estimation of a stress-strength model with non-identical component strengths under generalized progressive hybrid censoring scheme. Statistics, 55(2), 250–275. https://doi.org/10.1080/02331888.2021.1890739
   Web of Science ®Google Scholar
• Çetinkaya, Ç. (2021b). Reliability estimation of the stress-strength model with non-identical jointly type-II censored Weibull component strengths. Journal of Statistical Computation and Simulation, 91(14), 2917–2936. https://doi.org/10.1080/00949655.2021.1910948
   Web of Science ®Google Scholar
• Chang, G. J., Cu, L., & Hwang, F. K. (2000). Reliabilities of consecutive-k systems. Kluwer Academic Publishers.
   Google Scholar
• Chen, M. H., & Shao, Q. M. (1999). Monte Carlo estimation of Bayesian credible and HPD intervals. Journal of Computational and Graphical Statistics, 8(1), 69–92. https://doi.org/10.1080/10618600.1999.10474802
   Web of Science ®Google Scholar
• Chiang, D. T., & Niu, S. -C. (1981). Reliability of consecutive k-out-of n. F System IEEE Transactions on Reliability System IEEE Transactions on Reliability, 30(1), 87–89. https://doi.org/10.1109/TR.1981.5220981
   Web of Science ®Google Scholar
• Congdon, P. (2001). Bayesian statistical modeling. John Wiley.
   Google Scholar
• Demiray, D., & Z Laslan F, K. (2022). Stress-strength reliability estimation of a consecutive k-out-of-n system based on proportional hazard rate family. Journal of Statistical Computation and Simulation, 92(1), 159–190. https://doi.org/10.1080/00949655.2021.1935947
   Web of Science ®Google Scholar
• Dong, X., Zhang, L., & Li, F. (2013). Estimation of reliability for exponential distributions using ranked set sampling with unequal samples. Quality Technology & Quantitative Management, 10(3), 319–328. https://doi.org/10.1080/16843703.2013.11673417
   Web of Science ®Google Scholar
• Eryilmaz, S. (2008). Consecutive k-out-of-n: G system in stress-strength setup. Communications in Statistics -Simulation and Computation, 37(3), 579–589. https://doi.org/10.1080/03610910701678969
   Web of Science ®Google Scholar
• Eryilmaz, S. (2010). Review of recent advances in reliability of consecutive k-out-of-n and related systems. Journal of Risk and Reliability, 224(3), 225–237. https://doi.org/10.1243/1748006XJRR332
   Google Scholar
• Eryilmaz, S., & Demir, S. (2007). Success runs in a sequence of exchangeable binary trials. Journal of Statistical Planning and Inference, 137(9), 2954–2963. https://doi.org/10.1016/j.jspi.2006.10.015
   Web of Science ®Google Scholar
• Eryilmaz, S., & Devrim, Y. (2019). Theoretical derivation of wind plant power distribution with the consideration of wind turbine reliability. Reliability Engineering & System Safety, 185, 192–197. https://doi.org/10.1016/j.ress.2018.12.018
   Web of Science ®Google Scholar
• Gelman, A., & Rubin, D. B. (1992). Inference from iterative simulation using multiple sequences. Statistical Science, 7(4), 457–511. https://doi.org/10.1214/ss/1177011136
   Google Scholar
• Ghanbari, S., Roknabadi, A. R., & Salehi, M. (2022). Estimation of stress-strength reliability for Marshall–Olkin distributions based on progressively Type-II censored samples. Journal of Applied Statistics, 49(8), 1913–1934. https://doi.org/10.1080/02664763.2021.1884207
   PubMed Web of Science ®Google Scholar
• Gradshteyn, I. S., & Ryzhik, I. M. (1994). Table of integrals, series and products. Academic Press.
   Google Scholar
• Hassanein, W.A.A.E. -L., & Seyam, M. M. A. (2022). Structure of bivariate Rayleigh proportional hazard rate model with its associated copula applied on COVID-19 data. Quality and Reliability Engineering International, 38(7), 3451–3469. https://doi.org/10.1002/qre.3143
   PubMed Web of Science ®Google Scholar
• Kızılaslan, F., & Nadar, M. (2018). Estimation of reliability in a multicomponent stress–strength model based on a bivariate Kumaraswamy distribution. Statistical Papers, 59(1), 307–340. https://doi.org/10.1007/s00362-016-0765-8
   Web of Science ®Google Scholar
• Kohansal, A., Fernández, A. J., & Pérez-González, C. J. (2021). Multi-component stress-strength parameter estimation of a non-identical-component strengths system under the adaptive hybrid progressive censoring samples. Statistics, 55(4), 925–962. https://doi.org/10.1080/02331888.2021.1985499
   Web of Science ®Google Scholar
• Kotb, M. S., & Raqab, M. Z. (2021). Estimation of reliability for multi-component stress-strength model based on modified Weibull distribution. Stastical Papers, 62(6), 2763–2797. https://doi.org/10.1007/s00362-020-01213-0
   Web of Science ®Google Scholar
• Kuo, W., & Zuo, M. J. (2003). Optimal reliability modeling, principles and applications. Wiley.
   Google Scholar
• Lehmann, E. L. (1953). The power of rank test. Annals of Mathematical Statistics, 24(1), 23–43. https://doi.org/10.1214/aoms/1177729080
   Google Scholar
• Li, M., Hu, L., Peng, R., & Bai, Z. (2021). Reliability modeling for repairable circular consecutive-k-outof-n: F systems with retrial feature. Reliability Engineering & System Safety, 216, 107957. https://doi.org/10.1016/j.ress.2021.107957
   Web of Science ®Google Scholar
• Lindley, D. V. (1980). Approximate Bayes method. Trabajos de estadística y de investigación operativa, 31, 223–245.
   Google Scholar
• Marshall, A. W., & Olkin, I. (2007). Life distributions. Springer.
   Google Scholar
• Ozay, C., & Celiktas, M. S. (2016). Statistical analysis of wind speed using two-parameter Weibull distribution in Alaçat region. Energy Conversion and Management, 121, 49–54. https://doi.org/10.1016/j.enconman.2016.05.026
   Web of Science ®Google Scholar
• Pruim, R. (2021). CalvinBayes Public: R package for doing bayesian data analysis, Version 0.2.6. https://github.com/rpruim/CalvinBayes
   Google Scholar
• Quarda, T. B. M. J., Charron, C., & Chebana, F. (2016). Review of criteria for the selection of probability distributions for wind speed data and introduction of the moment and L-moment ratio diagram methods, with a case study. Energy Conversion and Management, 124, 247–265. https://doi.org/10.1016/j.enconman.2016.07.012
   Web of Science ®Google Scholar
• Rao, C. R. (1965). Linear statistical inference and its applications. Wiley.
   Google Scholar
• Rasethuntsa, T. R., & Nadar, M. (2018). Stress-strength reliability of a non-identical-component-strengths system based on upper record values from the family of Kumaraswamy generalized distributions. Statistics, 52(3), 684–716. https://doi.org/10.1080/02331888.2018.1435661
   Web of Science ®Google Scholar
• R Core Team. (2021). R: A language and environment for statistical computing, Version 4.1.1 and 4.1.2. R Foundation for Statistical Computing.
   Google Scholar
• Singh, D. P., Jha, M. K., Tripathi, Y., & Wang, L. (2022). Reliability estimation in a multicomponent stress-strength model for unit Burr III distribution under progressive censoring. Quality Technology & Quantitative Management, 19(5), 605–632. https://doi.org/10.1080/16843703.2022.2049508
   Web of Science ®Google Scholar
• Sparks, A. H. (2018). Nasapower: A NASA POWER global meteorology, surface solar energy and climatology data client for R. Journal of Open Source Software, 3(30), 1035. https://doi.org/10.21105/joss.01035
   Google Scholar
• Sparks, A. H. (2021). Nasapower: NASA-POWER Data from R. R package version 4.0.0, https://CRAN.R-project.org/package=nasapower.
   Google Scholar
• Tierney, L. (1994). Markov chains for exploring posterior distributions. The Annals of Statistics, 22(4), 1701–1728.
   Google Scholar
• Tripathi, Y. M., Petropoulos, C., & Jha, M. K. (2022). Estimation of P(Y<X) for lognormal distribution. Quality Technology & Quantitative Management, 19(6), 749–765. https://doi.org/10.1080/16843703.2022.2052585
   Web of Science ®Google Scholar
• Wang, B. X., Jiang, P. H., & Wang, X. (2019). The stress-strength models for the proportional hazards family and proportional reverse hazards family. In Y. Lio, H. Ng, T. R. Tsai, & D. G. Chen (Eds.), Statistical quality technologies: Theory and practice (pp. 277–295). Springer. https://link.springer.com/chapter/10.1007/978-3-030-20709-0_12#chapter-info
   Google Scholar
• Wang, D., Si, S., Cai, Z., & Zhao, J. (2021). Reliability optimization of linear consecutive-k-out-of-n: F systems driven by reconfigurable importance. Reliability Engineering & System Safety, 216, 107994. https://doi.org/10.1016/j.ress.2021.107994
   Web of Science ®Google Scholar
• Wang, L., Wu, K., Tripathi, Y. M., & Lodhi, C. (2022). Reliability analysis of multicomponent stress-strength reliability from a bathtub-shaped distribution. Journal of Applied Statistics, 49(1), 122–142. https://doi.org/10.1080/02664763.2020.1803808
   PubMed Web of Science ®Google Scholar