IDEAS home Printed from https://ideas.repec.org/a/spr/stpapr/v65y2024i8d10.1007_s00362-024-01588-4.html
   My bibliography  Save this article

Estimation of multicomponent system reliability for inverse Weibull distribution using survival signature

Author

Listed:
  • Nabakumar Jana

    (Indian Institute of Technology (ISM) Dhanbad)

  • Samadrita Bera

    (Indian Institute of Technology (ISM) Dhanbad)

Abstract

The problem of estimating multicomponent stress-strength reliability $$R_{k,n}$$ R k , n for two-parameter inverse Weibull distributions under progressive type-II censoring is considered. We derive maximum likelihood estimator, Bayes estimator and generalised confidence interval of $$R_{k,n}$$ R k , n when all parameters are unknown. We study the reliability of stress-strength system with multiple types of components using signature-based approach. When different types of random stresses are acting on a compound system, we derive MLE, maximum spacing estimator of multi-state reliability. Using generalized pivotal quantity, the generalized confidence interval and percentile bootstrap intervals of the reliability are derived. Under a common stress subjected to the system, we also derive the estimators of the reliability parameter. Different point estimators and generalized, bootstrap confidence intervals of the reliability are developed. Risk comparison of the classical and Bayes estimators is carried out using Monte-Carlo simulation. Application of the proposed estimators is shown using real-life data sets.

Suggested Citation

  • Nabakumar Jana & Samadrita Bera, 2024. "Estimation of multicomponent system reliability for inverse Weibull distribution using survival signature," Statistical Papers, Springer, vol. 65(8), pages 5077-5108, October.
  • Handle: RePEc:spr:stpapr:v:65:y:2024:i:8:d:10.1007_s00362-024-01588-4
    DOI: 10.1007/s00362-024-01588-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00362-024-01588-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00362-024-01588-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nabakumar Jana & Somesh Kumar & Kashinath Chatterjee, 2016. "Bayes estimation for exponential distributions with common location parameter and applications to multi-state reliability models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(15), pages 2697-2712, November.
    2. M. S. Kotb & M. Z. Raqab, 2021. "Estimation of reliability for multi-component stress–strength model based on modified Weibull distribution," Statistical Papers, Springer, vol. 62(6), pages 2763-2797, December.
    3. Subhash Kochar & Hari Mukerjee & Francisco J. Samaniego, 1999. "The “signature” of a coherent system and its application to comparisons among systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 46(5), pages 507-523, August.
    4. Jana, Nabakumar & Bera, Samadrita, 2022. "Interval estimation of multicomponent stress–strength reliability based on inverse Weibull distribution," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 191(C), pages 95-119.
    5. Keming Yu & Bing Wang & Valentin Patilea, 2013. "New estimating equation approaches with application in lifetime data analysis," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(3), pages 589-615, June.
    6. Francisco J. Samaniego, 2007. "System Signatures and their Applications in Engineering Reliability," International Series in Operations Research and Management Science, Springer, number 978-0-387-71797-5, April.
    7. Louis J. M. Aslett & Frank P. A. Coolen & Simon P. Wilson, 2015. "Bayesian Inference for Reliability of Systems and Networks Using the Survival Signature," Risk Analysis, John Wiley & Sons, vol. 35(9), pages 1640-1651, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hindolo George-Williams & Geng Feng & Frank PA Coolen & Michael Beer & Edoardo Patelli, 2019. "Extending the survival signature paradigm to complex systems with non-repairable dependent failures," Journal of Risk and Reliability, , vol. 233(4), pages 505-519, August.
    2. Weiyong Ding & Rui Fang & Peng Zhao, 2017. "Relative Aging of Coherent Systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(4), pages 345-354, June.
    3. Jia, Xujie & Shen, Jingyuan & Xu, Fanqi & Ma, Ruihong & Song, Xueying, 2019. "Modular decomposition signature for systems with sequential failure effect," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 435-444.
    4. Serkan Eryilmaz, 2014. "A new look at dynamic behavior of binary coherent system from a state-level perspective," Annals of Operations Research, Springer, vol. 212(1), pages 115-125, January.
    5. Sadiya & Mangey Ram & Akshay Kumar, 2022. "A New Approach to Compute System Reliability with Three-Serially Linked Modules," Mathematics, MDPI, vol. 11(1), pages 1-18, December.
    6. Burkschat, M. & Samaniego, F.J., 2018. "Dynamic IFR concepts for coherent systems," Statistics & Probability Letters, Elsevier, vol. 142(C), pages 1-7.
    7. Liling Ge & Yingjie Zhang, 2019. "Improving operational reliability of manufacturing systems by process optimization via survival signatures," Journal of Risk and Reliability, , vol. 233(3), pages 444-454, June.
    8. M. Kelkin Nama & M. Asadi, 2014. "Stochastic Properties of Components in a Used Coherent System," Methodology and Computing in Applied Probability, Springer, vol. 16(3), pages 675-691, September.
    9. Markos V. Koutras & Ioannis S. Triantafyllou & Serkan Eryilmaz, 2016. "Stochastic Comparisons Between Lifetimes of Reliability Systems with Exchangeable Components," Methodology and Computing in Applied Probability, Springer, vol. 18(4), pages 1081-1095, December.
    10. A. Toomaj & M. Doostparast, 2016. "On the Kullback Leibler information for mixed systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(10), pages 2458-2465, July.
    11. Yandan Yang & Hon Keung Tony Ng & Narayanaswamy Balakrishnan, 2019. "Expectation–maximization algorithm for system-based lifetime data with unknown system structure," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(1), pages 69-98, March.
    12. Huang, Xianzhen & Aslett, Louis J.M. & Coolen, Frank P.A., 2019. "Reliability analysis of general phased mission systems with a new survival signature," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 416-422.
    13. Tavangar, Mahdi & Hashemi, Marzieh, 2022. "Reliability and maintenance analysis of coherent systems subject to aging and environmental shocks," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    14. Serkan Eryilmaz & Altan Tuncel, 2016. "Generalizing the survival signature to unrepairable homogeneous multi‐state systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(8), pages 593-599, December.
    15. Ioannis S. Triantafyllou, 2022. "Signature-Based Analysis of the Weighted- r -within-Consecutive- k -out-of- n : F Systems," Mathematics, MDPI, vol. 10(15), pages 1-13, July.
    16. Jingwen Lu & He Yi & Xiang Li & Narayanaswamy Balakrishnan, 2023. "Joint Reliability of Two Consecutive-(1, l) or (2, k)-out-of-(2, n): F Type Systems and Its Application in Smart Street Light Deployment," Methodology and Computing in Applied Probability, Springer, vol. 25(1), pages 1-26, March.
    17. Roy Cerqueti, 2022. "A new concept of reliability system and applications in finance," Annals of Operations Research, Springer, vol. 312(1), pages 45-64, May.
    18. Siddhartha Chakraborty & Biswabrata Pradhan, 2024. "On cumulative residual extropy of coherent and mixed systems," Annals of Operations Research, Springer, vol. 340(1), pages 59-81, September.
    19. Qin, Jinlei & Coolen, Frank P.A., 2022. "Survival signature for reliability evaluation of a multi-state system with multi-state components," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    20. Yi, He & Cui, Lirong & Balakrishnan, Narayanaswamy, 2021. "Computation of survival signatures for multi-state consecutive-k systems," Reliability Engineering and System Safety, Elsevier, vol. 208(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:stpapr:v:65:y:2024:i:8:d:10.1007_s00362-024-01588-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.