IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v312y2022i1d10.1007_s10479-020-03852-w.html
   My bibliography  Save this article

A new framework of complex system reliability with imperfect maintenance policy

Author

Listed:
  • Mengmeng Zhu

    (North Carolina State University)

Abstract

The interactions and dependencies between software and hardware are often neglected in modeling system reliability in the past few decades due to the mathematical complexity. However, many system failures occurred from the interactions or simultaneous occurrences of software and hardware. This paper first proposes a new diagram of categorizing system-level failures and further incorporates such a diagram into the development of complex system reliability framework. System-level failures result from software subsystem, hardware subsystem, and the interactions of software and hardware subsystems. The focus of this study is on the investigation of the interactions failures generated from the interactions of software and hardware subsystems. In addition to the considerations of total hardware failures, software-induced hardware failures, and hardware-induced software failures introduced by Zhu and Pham (Mathematics 7(11):1049, 2019), we further introduce the partial hardware failures that can be respectively induced by hardware and software to explicitly demonstrate the dependencies and interactions between software and hardware. Hence, a new complex system reliability framework is developed based on such system-level failure categorization with the Markov process. Furthermore, the numerical examples are studied to illustrate the impacts on system reliability with the changes of state transition parameters that modeling the interactions of software and hardware subsystems. Finally, we have studied two maintenance policies of the proposed complex system reliability model.

Suggested Citation

  • Mengmeng Zhu, 2022. "A new framework of complex system reliability with imperfect maintenance policy," Annals of Operations Research, Springer, vol. 312(1), pages 553-579, May.
    • Handle: RePEc:spr:annopr:v:312:y:2022:i:1:d:10.1007_s10479-020-03852-w
    DOI: 10.1007/s10479-020-03852-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-020-03852-w
    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/s10479-020-03852-w?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. Hoang Pham, 2006. "Software Reliability Modeling," Springer Series in Reliability Engineering, in: System Software Reliability, chapter 5, pages 153-177, Springer.
    2. Z. Sinuany-Stern, 1999. "Reliability and maintenance in production control ‐ an introduction," Annals of Operations Research, Springer, vol. 91(0), pages 1-10, January.
    3. Mengmeng Zhu & Hoang Pham, 2019. "A Novel System Reliability Modeling of Hardware, Software, and Interactions of Hardware and Software," Mathematics, MDPI, vol. 7(11), pages 1-14, November.
    4. Hoang Pham & Hongzhou Wang, 2000. "Optimal (τ, T) opportunistic maintenance of a k‐out‐of‐n:G system with imperfect PM and partial failure," Naval Research Logistics (NRL), John Wiley & Sons, vol. 47(3), pages 223-239, April.
    5. Yuka Minamino & Shinji Inoue & Shigeru Yamada, 2016. "NHPP-based change-point modeling for software reliability assessment and its application to software development management," Annals of Operations Research, Springer, vol. 244(1), pages 85-101, September.
    6. Wang, Jia & Bai, Guanghan & Li, Zhigang & Zuo, Ming J., 2020. "A general discrete degradation model with fatal shocks and age- and state-dependent nonfatal shocks," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    7. Mengmeng Zhu & Hoang Pham, 2018. "A multi-release software reliability modeling for open source software incorporating dependent fault detection process," Annals of Operations Research, Springer, vol. 269(1), pages 773-790, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Dahye Lee & Inhong Chang & Hoang Pham, 2023. "Study of a New Software Reliability Growth Model under Uncertain Operating Environments and Dependent Failures," Mathematics, MDPI, vol. 11(18), pages 1-17, September.

    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. Nupur Goyal & Vikas Kumar Roy & Mangey Ram, 2022. "Mathematical modelling of embedded systems under network failures," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(2), pages 604-614, April.
    2. P. K. Kapur & Saurabh Panwar & Ompal Singh & Vivek Kumar, 2022. "Joint optimization of software time-to-market and testing duration using multi-attribute utility theory," Annals of Operations Research, Springer, vol. 312(1), pages 305-332, May.
    3. Mengmeng Zhu & Hoang Pham, 2019. "A Novel System Reliability Modeling of Hardware, Software, and Interactions of Hardware and Software," Mathematics, MDPI, vol. 7(11), pages 1-14, November.
    4. Luo, Ming & Wu, Shaomin, 2019. "A comprehensive analysis of warranty claims and optimal policies," European Journal of Operational Research, Elsevier, vol. 276(1), pages 144-159.
    5. Vibha Verma & Sameer Anand & P. K. Kapur & Anu G. Aggarwal, 2022. "Unified framework to assess software reliability and determine optimal release time in presence of fault reduction factor, error generation and fault removal efficiency," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2429-2441, October.
    6. Lyu, Dongzhen & Niu, Guangxing & Liu, Enhui & Zhang, Bin & Chen, Gang & Yang, Tao & Zio, Enrico, 2022. "Time space modelling for fault diagnosis and prognosis with uncertainty management: A general theoretical formulation," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    7. Xiao Yu & Armagan Bayram, 2021. "Managing capacity for virtual and office appointments in chronic care," Health Care Management Science, Springer, vol. 24(4), pages 742-767, December.
    8. Avinash K. Shrivastava & Vivek Kumar & P. K. Kapur & Ompal Singh, 0. "Software release and testing stop time decision with change point," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 0, pages 1-12.
    9. Sarang Deo & Seyed Iravani & Tingting Jiang & Karen Smilowitz & Stephen Samuelson, 2013. "Improving Health Outcomes Through Better Capacity Allocation in a Community-Based Chronic Care Model," Operations Research, INFORMS, vol. 61(6), pages 1277-1294, December.
    10. Mengmeng Zhu & Hoang Pham, 2022. "A generalized multiple environmental factors software reliability model with stochastic fault detection process," Annals of Operations Research, Springer, vol. 311(1), pages 525-546, April.
    11. Triet Pham & Hoang Pham, 2019. "A generalized software reliability model with stochastic fault-detection rate," Annals of Operations Research, Springer, vol. 277(1), pages 83-93, June.
    12. Sourav Sinha & Neeraj Kumar Goyal & Rajib Mall, 2019. "Survey of combined hardware–software reliability prediction approaches from architectural and system failure viewpoint," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(4), pages 453-474, August.
    13. Subhashis Chatterjee & Ankur Shukla & Hoang Pham, 2019. "Modeling and analysis of software fault detectability and removability with time variant fault exposure ratio, fault removal efficiency, and change point," Journal of Risk and Reliability, , vol. 233(2), pages 246-256, April.
    14. Wang, Jia & Han, Xu & Zhang, Yun-an & Bai, Guanghan, 2021. "Modeling the varying effects of shocks for a multi-stage degradation process," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    15. Hashemi, M. & Asadi, M. & Zarezadeh, S., 2020. "Optimal maintenance policies for coherent systems with multi-type components," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    16. Pang, Zhenan & Li, Tianmei & Pei, Hong & Si, Xiaosheng, 2023. "A condition-based prognostic approach for age- and state-dependent partially observable nonlinear degrading system," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    17. Avinash K. Shrivastava & Vivek Kumar & P. K. Kapur & Ompal Singh, 2020. "Software release and testing stop time decision with change point," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(2), pages 196-207, July.
    18. Michael Patriksson & Ann-Brith Strömberg & Adam Wojciechowski, 2015. "The stochastic opportunistic replacement problem, part II: a two-stage solution approach," Annals of Operations Research, Springer, vol. 224(1), pages 51-75, January.
    19. Subhashis Chatterjee & Ankur Shukla, 2017. "An Ideal Software Release Policy for an Improved Software Reliability Growth Model Incorporating Imperfect Debugging with Fault Removal Efficiency and Change Point," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(03), pages 1-21, June.
    20. Jia Huang & Hu-Chen Liu & Chun-Yan Duan & Ming-Shun Song, 2022. "An improved reliability model for FMEA using probabilistic linguistic term sets and TODIM method," Annals of Operations Research, Springer, vol. 312(1), pages 235-258, May.

    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:annopr:v:312:y:2022:i:1:d:10.1007_s10479-020-03852-w. 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.