IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v15y2024i8d10.1007_s13198-024-02384-x.html
   My bibliography  Save this article

Availability and cost analysis of a multistage, multi-evaporator type compressor

Author

Listed:
  • Surbhi Gupta

    (Amity University)

  • H. D. Arora

    (Amity University)

  • Anjali Naithani

    (Amity University)

Abstract

Refrigeration is a critical component of thermal environment engineering. The process of removing heat from a substance under precise conditions is referred to as refrigeration. It also includes the process of lowering and maintaining a body's temperature below the ambient temperature. In this paper, we examine the availability and cost function of the system of the Refrigeration plant. This system has three modes: normal, degraded, and failed. The system is divided into four sections: A (Compressor), B (Condenser), C (two standby expansion valves), and D. (three evaporators in series). A standby expansion valve is installed to improve the performance of the refrigeration plant. The supplementary variable technique is used to obtain state probabilities and the inversion process is used to obtain the expression of operational availability and profit functions. The MTTF (mean time to failure) is also estimated. A numerical example is presented with a graphical presentation to illustrate the practical advantages of the model.

Suggested Citation

  • Surbhi Gupta & H. D. Arora & Anjali Naithani, 2024. "Availability and cost analysis of a multistage, multi-evaporator type compressor," 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. 15(8), pages 3869-3877, August.
    • Handle: RePEc:spr:ijsaem:v:15:y:2024:i:8:d:10.1007_s13198-024-02384-x
    DOI: 10.1007/s13198-024-02384-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-024-02384-x
    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/s13198-024-02384-x?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. Zengkai Liu & Yonghong Liu & Baoping Cai, 2014. "Reliability Analysis of the Electrical Control System of Subsea Blowout Preventers Using Markov Models," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-9, November.
    2. Qingliang Zeng & Wenting Liu & Lirong Wan & Chenglong Wang & Kuidong Gao, 2020. "Maintenance Strategy Based on Reliability Analysis and FMEA: A Case Study for Hydraulic Cylinders of Traditional Excavators with ERRS," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-11, November.
    3. Toshio Nakagawa, 2005. "Maintenance Theory of Reliability," Springer Series in Reliability Engineering, Springer, number 978-1-84628-221-8, July.
    4. Lisnianski, Anatoly & Elmakias, David & Laredo, David & Ben Haim, Hanoch, 2012. "A multi-state Markov model for a short-term reliability analysis of a power generating unit," Reliability Engineering and System Safety, Elsevier, vol. 98(1), pages 1-6.
    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. 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).
    2. Juan Eloy Ruiz-Castro, 2021. "Optimizing a Multi-State Cold-Standby System with Multiple Vacations in the Repair and Loss of Units," Mathematics, MDPI, vol. 9(8), pages 1-29, April.
    3. Chin-Chih Chang, 2023. "Optimal maintenance policy for a k-out-of-n system with replacement first and last," Annals of Operations Research, Springer, vol. 323(1), pages 31-43, April.
    4. Stanisław Duer & Marek Woźniak & Jacek Paś & Konrad Zajkowski & Arkadiusz Ostrowski & Marek Stawowy & Zbigniew Budniak, 2023. "Reliability Testing of Wind Farm Devices Based on the Mean Time to Failures," Energies, MDPI, vol. 16(6), pages 1-13, March.
    5. Finkelstein, Maxim & Cha, Ji Hwan & Langston, Amy, 2023. "Improving classical optimal age-replacement policies for degrading items," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    6. Ali, Sajid & Pievatolo, Antonio, 2018. "Time and magnitude monitoring based on the renewal reward process," Reliability Engineering and System Safety, Elsevier, vol. 179(C), pages 97-107.
    7. Pérez Ramírez, Pedro A. & Utne, Ingrid Bouwer, 2013. "Decision support for life extension of technical systems through virtual age modelling," Reliability Engineering and System Safety, Elsevier, vol. 115(C), pages 55-69.
    8. Torrado, Nuria, 2022. "Optimal component-type allocation and replacement time policies for parallel systems having multi-types dependent components," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    9. Shafiee, Mahmood & Chukova, Stefanka, 2013. "Maintenance models in warranty: A literature review," European Journal of Operational Research, Elsevier, vol. 229(3), pages 561-572.
    10. Ivan Postnikov & Ekaterina Samarkina & Andrey Penkovskii & Vladimir Kornev & Denis Sidorov, 2023. "Modeling Unpredictable Behavior of Energy Facilities to Ensure Reliable Operation in a Cyber-Physical System," Energies, MDPI, vol. 16(19), pages 1-11, October.
    11. Asadi, Majid, 2023. "On a parametric model for the mean number of system repairs with applications," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    12. Zhao, Xufeng & Al-Khalifa, Khalifa N. & Magid Hamouda, Abdel & Nakagawa, Toshio, 2017. "Age replacement models: A summary with new perspectives and methods," Reliability Engineering and System Safety, Elsevier, vol. 161(C), pages 95-105.
    13. Stanisław Duer & Marek Woźniak & Jacek Paś & Konrad Zajkowski & Dariusz Bernatowicz & Arkadiusz Ostrowski & Zbigniew Budniak, 2023. "Reliability Testing of Wind Farm Devices Based on the Mean Time between Failures (MTBF)," Energies, MDPI, vol. 16(4), pages 1-16, February.
    14. Ji Hwan Cha & Maxim Finkelstein, 2020. "On optimal life extension for degrading systems," Journal of Risk and Reliability, , vol. 234(3), pages 487-495, June.
    15. Ji Hwan Cha & Maxim Finkelstein & Gregory Levitin, 2022. "Replacement Policy for Heterogeneous Items Subject to Gamma Degradation Processes," Methodology and Computing in Applied Probability, Springer, vol. 24(3), pages 1323-1340, September.
    16. Eryilmaz, Serkan, 2020. "Age-based preventive maintenance for coherent systems with applications to consecutive-k-out-of-n and related systems," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    17. Zhang, Cai Wen & Zhang, Tieling & Chen, Nan & Jin, Tongdan, 2013. "Reliability modeling and analysis for a novel design of modular converter system of wind turbines," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 86-94.
    18. Safaei, Fatemeh & Taghipour, Sharareh, 2024. "Integrated degradation-based burn-in and maintenance model for heterogeneous and highly reliable items," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    19. María Luz Gámiz & Delia Montoro-Cazorla & María del Carmen Segovia-García & Rafael Pérez-Ocón, 2022. "MoMA Algorithm: A Bottom-Up Modeling Procedure for a Modular System under Environmental Conditions," Mathematics, MDPI, vol. 10(19), pages 1-19, September.
    20. Sang-Hyun Kim, 2015. "Time to Come Clean? Disclosure and Inspection Policies for Green Production," Operations Research, INFORMS, vol. 63(1), pages 1-20, February.

    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:ijsaem:v:15:y:2024:i:8:d:10.1007_s13198-024-02384-x. 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.