IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i16p5774-d883730.html
   My bibliography  Save this article

Fault Identification and Fault Impact Analysis of The Vapor Compression Refrigeration Systems in Buildings: A System Reliability Approach

Author

Listed:
  • Mostafa Fadaeefath Abadi

    (Department of Building, Civil and Environmental Engineering (BCEE), Gina Cody School of Engineering and Computer Science, Concordia University, Montréal, QC H3G 1M8, Canada)

  • Mohammad Hosseini Rahdar

    (Department of Building, Civil and Environmental Engineering (BCEE), Gina Cody School of Engineering and Computer Science, Concordia University, Montréal, QC H3G 1M8, Canada)

  • Fuzhan Nasiri

    (Department of Building, Civil and Environmental Engineering (BCEE), Gina Cody School of Engineering and Computer Science, Concordia University, Montréal, QC H3G 1M8, Canada)

  • Fariborz Haghighat

    (Department of Building, Civil and Environmental Engineering (BCEE), Gina Cody School of Engineering and Computer Science, Concordia University, Montréal, QC H3G 1M8, Canada)

Abstract

The Vapor Compression Refrigeration System (VCRS) is one of the most critical systems in buildings typically used in Heating, Ventilation, and Air Conditioning (HVAC) systems in residential and industrial sections. Therefore, identifying their faults and evaluating their reliability are essential to ensure the required operations and performance in these systems. Various components and subsystems are included in the VCRS, which need to be analyzed for system reliability. This research’s objective is conducting a comprehensive system reliability analysis on the VCRS by focusing on fault identification and determining the fault impacts on these systems. A typical VCRS in an office building is selected for this research regarding this objective. The corresponding reliability data, including the probability distributions and parameters, are collected from references to perform the reliability evaluation on the components and subsystems of the VCRS. Then the optimum distribution parameters have been obtained in the next step as the main findings. Additionally, by applying optimization techniques, efforts have been taken to maximize the system’s reliability. Finally, a comparison between the primary and the optimized systems (with new distribution parameters) has been performed over their lifetime to illustrate the system’s improvement percentage.

Suggested Citation

  • Mostafa Fadaeefath Abadi & Mohammad Hosseini Rahdar & Fuzhan Nasiri & Fariborz Haghighat, 2022. "Fault Identification and Fault Impact Analysis of The Vapor Compression Refrigeration Systems in Buildings: A System Reliability Approach," Energies, MDPI, vol. 15(16), pages 1-21, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:16:p:5774-:d:883730
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/16/5774/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/16/5774/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hamed Ahmadzade & Rong Gao, 2018. "Reversed hazard function of uncertain lifetime," Fuzzy Optimization and Decision Making, Springer, vol. 17(4), pages 387-400, December.
    2. Ilia Frenkel & Lev Khvatskin, 2012. "Reliability Decisions for Supermarket Refrigeration System by using Combined Stochastic Process and Universal Generating Function Method: Case Study," Springer Series in Reliability Engineering, in: Anatoly Lisnianski & Ilia Frenkel (ed.), Recent Advances in System Reliability, chapter 0, pages 97-112, Springer.
    3. Hengjie Zhang & Yucheng Dong & Jing Xiao & Francisco Chiclana & Enrique Herrera-Viedma, 2020. "Personalized individual semantics-based approach for linguistic failure modes and effects analysis with incomplete preference information," IISE Transactions, Taylor & Francis Journals, vol. 52(11), pages 1275-1296, November.
    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. Peng Wu & Jinpei Liu & Ligang Zhou & Huayou Chen, 2022. "An Integrated Group Decision-Making Method with Hesitant Qualitative Information Based on DEA Cross-Efficiency and Priority Aggregation for Evaluating Factors Affecting a Resilient City," Group Decision and Negotiation, Springer, vol. 31(2), pages 293-316, April.
    2. Kamilla Marchewka-Bartkowiak & Karolina Anna Nowak & Michał Litwiński, 2022. "Digital valuation of personality using personal tokens," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1555-1576, September.
    3. Li, Cong-Cong & Dong, Yucheng & Liang, Haiming & Pedrycz, Witold & Herrera, Francisco, 2022. "Data-driven method to learning personalized individual semantics to support linguistic multi-attribute decision making," Omega, Elsevier, vol. 111(C).
    4. Suvojit Dhara & Adrijit Goswami, 2023. "Causal Relationship and Ranking Technique (CRRT): A Novel Group Decision-Making Model and Application in Students’ Performance Assessment in Indian High School Context," Group Decision and Negotiation, Springer, vol. 32(4), pages 835-870, August.
    5. Zhang, Hengjie & Dong, Yucheng & Xiao, Jing & Chiclana, Francisco & Herrera-Viedma, Enrique, 2021. "Consensus and opinion evolution-based failure mode and effect analysis approach for reliability management in social network and uncertainty contexts," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    6. Chuanhao Fan & Yan Chen & Yan Zhu & Long Zhang & Wenjuan Wu & Bin Ling & Sijie Tang, 2022. "Using Fuzzy Comprehensive Evaluation to Assess the Competency of Full-Time Water Conservancy Emergency Rescue Teams," Mathematics, MDPI, vol. 10(12), pages 1-25, June.
    7. Li, Ying & Liu, Peide & Li, Gang, 2023. "An asymmetric cost consensus based failure mode and effect analysis method with personalized risk attitude information," Reliability Engineering and System Safety, Elsevier, vol. 235(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:gam:jeners:v:15:y:2022:i:16:p:5774-:d:883730. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.