IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v229y2023ics095183202200494x.html
   My bibliography  Save this article

Reliability acceptance sampling plan for degraded products subject to Wiener process with unit heterogeneity

Author

Listed:
  • Zheng, Huiling
  • Yang, Jun
  • Xu, Houbao
  • Zhao, Yu

Abstract

The acceptance sampling plan (ASP), designed with the degradation data following the Wiener process, is widely used to verify the reliability requirements of products. Previous studies mainly designed ASPs under the given sampling plan, which lacked the justification of the sampling plan; furthermore, they ignored the unit heterogeneity of products in the degradation modeling, which affects the description accuracy of risks. To solve the above problems, this paper proposes an optimal ASP design method considering the unit heterogeneity. Firstly, the determinant of the Fisher information matrix is used to characterize the parameters estimation accuracy, under the cost requirement, the optimal test time and sample size are determined by maximizing the determinant, and an optimal sampling plan is obtained. Then, with the likelihood ratio order and the monotonicity of the average failure time on the average degradation rate, the average degradation rate is taken as the acceptance index to effectively simplify the original acceptance test problem. On this basis, the decision-making criterion considering the existence of ASP is obtained by solving the risk constraint equations of both parties. Finally, the simulation and a real example are presented to demonstrate the implementation and feasibility of the proposed method.

Suggested Citation

  • Zheng, Huiling & Yang, Jun & Xu, Houbao & Zhao, Yu, 2023. "Reliability acceptance sampling plan for degraded products subject to Wiener process with unit heterogeneity," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
  • Handle: RePEc:eee:reensy:v:229:y:2023:i:c:s095183202200494x
    DOI: 10.1016/j.ress.2022.108877
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S095183202200494X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2022.108877?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. Zhang, Chunhua & Lu, Xiang & Tan, Yuanyuan & Wang, Yashun, 2015. "Reliability demonstration methodology for products with Gamma Process by optimal accelerated degradation testing," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 369-377.
    2. Khalil, Y.F., 2019. "New statistical formulations for determination of qualification test plans of safety instrumented systems (SIS) subject to low/high operational demands," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 196-209.
    3. Wang, Yueyao & Lee, I-Chen & Hong, Yili & Deng, Xinwei, 2022. "Building degradation index with variable selection for multivariate sensory data," Reliability Engineering and System Safety, Elsevier, vol. 227(C).
    4. Cai, Xia & Tian, Yubin & Ning, Wei, 2019. "Change-point analysis of the failure mechanisms based on accelerated life tests," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 515-522.
    5. Wu, Shuo-Jye & Hsu, Chu-Chun & Huang, Syuan-Rong, 2020. "Optimal designs and reliability sampling plans for one-shot devices with cost considerations," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    6. Cheng, Yao & Liao, Haitao & Huang, Zhiyi, 2021. "Optimal degradation-based hybrid double-stage acceptance sampling plan for a heterogeneous product," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    7. Kim, Seong-Joon & Mun, Byeong Min & Bae, Suk Joo, 2019. "A cost-driven reliability demonstration plan based on accelerated degradation tests," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 226-239.
    8. Gao, Hongda & Cui, Lirong & Dong, Qinglai, 2020. "Reliability modeling for a two-phase degradation system with a change point based on a Wiener process," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    9. Devireddy Charana Udaya Sivakumar & Rosaiah Kanaparthi & Gadde Srinivasa Rao & Kruthiventi Kalyani, 2019. "The Odd Generalized Exponential Log-Logistic Distribution Group Acceptance Sampling Plan," Statistics in Transition New Series, Polish Statistical Association, vol. 20(1), pages 103-116, March.
    10. Jung, Yongsu & Lee, Ikjin, 2021. "Optimal design of experiments for optimization-based model calibration using Fisher information matrix," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    11. Ji Hwan Cha & F. G. Badía, 2021. "Variables acceptance reliability sampling plan based on degradation test," Statistical Papers, Springer, vol. 62(5), pages 2227-2245, October.
    12. Li, Xiaoyang & Chen, Wenbin & Sun, Fuqiang & Liao, Haitao & Kang, Rui & Li, Renqing, 2018. "Bayesian accelerated acceptance sampling plans for a lognormal lifetime distribution under Type-I censoring," Reliability Engineering and System Safety, Elsevier, vol. 171(C), pages 78-86.
    13. Zheng, Huiling & Kong, Xuefeng & Xu, Houbao & Yang, Jun, 2021. "Reliability analysis of products based on proportional hazard model with degradation trend and environmental factor," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    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. Cheng, Yao & Liao, Haitao & Huang, Zhiyi, 2021. "Optimal degradation-based hybrid double-stage acceptance sampling plan for a heterogeneous product," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    2. Starling, James K. & Mastrangelo, Christina & Choe, Youngjun, 2021. "Improving Weibull distribution estimation for generalized Type I censored data using modified SMOTE," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    3. Pedersen, Tom Ivar & Liu, Xingheng & Vatn, Jørn, 2023. "Maintenance optimization of a system subject to two-stage degradation, hard failure, and imperfect repair," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    4. Zhu, Xiaojun & Balakrishnan, N., 2022. "One-shot device test data analysis using non-parametric and semi-parametric inferential methods and applications," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    5. Khalil, Y.F., 2019. "New statistical formulations for determination of qualification test plans of safety instrumented systems (SIS) subject to low/high operational demands," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 196-209.
    6. Yaping Li & Enrico Zio & Ershun Pan, 2021. "An MEWMA-based segmental multivariate hidden Markov model for degradation assessment and prediction," Journal of Risk and Reliability, , vol. 235(5), pages 831-844, October.
    7. Huang, Jianlin & Golubović, Dušan S & Koh, Sau & Yang, Daoguo & Li, Xiupeng & Fan, Xuejun & Zhang, G.Q., 2016. "Lumen degradation modeling of white-light LEDs in step stress accelerated degradation test," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 152-159.
    8. Ma, Jie & Cai, Li & Liao, Guobo & Yin, Hongpeng & Si, Xiaosheng & Zhang, Peng, 2023. "A multi-phase Wiener process-based degradation model with imperfect maintenance activities," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    9. Wang, Huan & Wang, Guan-jun & Duan, Feng-jun, 2016. "Planning of step-stress accelerated degradation test based on the inverse Gaussian process," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 97-105.
    10. Fang, Chen & Cui, Lirong, 2021. "Balanced Systems by Considering Multi-state Competing Risks Under Degradation Processes," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    11. Sun, Bo & Fan, Xuejun & Ye, Huaiyu & Fan, Jiajie & Qian, Cheng & van Driel, Williem & Zhang, Guoqi, 2017. "A novel lifetime prediction for integrated LED lamps by electronic-thermal simulation," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 14-21.
    12. Han, David & Bai, Tianyu, 2020. "Design optimization of a simple step-stress accelerated life test – Contrast between continuous and interval inspections with non-uniform step durations," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    13. Wang, Yueyao & Lee, I-Chen & Hong, Yili & Deng, Xinwei, 2022. "Building degradation index with variable selection for multivariate sensory data," Reliability Engineering and System Safety, Elsevier, vol. 227(C).
    14. Song, Wanqing & Duan, Shouwu & Zio, Enrico & Kudreyko, Aleksey, 2022. "Multifractional and long-range dependent characteristics for remaining useful life prediction of cracking gas compressor," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    15. Chen, Zhen & Li, Yaping & Zhou, Di & Xia, Tangbin & Pan, Ershun, 2021. "Two-phase degradation data analysis with change-point detection based on Gaussian process degradation model," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    16. Xu, Dong & Tian, Yubin & Shi, Junbiao & Wang, Dianpeng & Zhang, Ming & Li, Haijin, 2023. "Reliability analysis and optimal redundancy for a satellite power supply system based on a new dynamic k-out-of-n: G model," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    17. Ji Hwan Cha & Maxim Finkelstein, 2023. "Acceptance reliability sampling plan for items from heterogeneous populations," Journal of Risk and Reliability, , vol. 237(6), pages 1199-1208, December.
    18. Bin Suo & Yang Qi & Kai Sun & Jingyuan Xu, 2023. "A Novel Model Validation Method Based on Area Metric Disagreement between Accelerated Storage Distributions and Natural Storage Data," Mathematics, MDPI, vol. 11(11), pages 1-18, May.
    19. Vrignat, Pascal & Kratz, Frédéric & Avila, Manuel, 2022. "Sustainable manufacturing, maintenance policies, prognostics and health management: A literature review," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    20. Lu, Yaohui & Zheng, Heyan & Zeng, Jing & Chen, Tianli & Wu, Pingbo, 2019. "Fatigue life reliability evaluation in a high-speed train bogie frame using accelerated life and numerical test," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 221-232.

    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:eee:reensy:v:229:y:2023:i:c:s095183202200494x. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.