IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i19p10842-d646538.html
   My bibliography  Save this article

Influence of Disinfectants on Airport Conveyor Belts

Author

Listed:
  • Katarína Draganová

    (Faculty of Aeronautics, Technical University of Košice, Rampová 7, 041 21 Košice, Slovakia)

  • Karol Semrád

    (Faculty of Aeronautics, Technical University of Košice, Rampová 7, 041 21 Košice, Slovakia)

  • Monika Blišťanová

    (Faculty of Aeronautics, Technical University of Košice, Rampová 7, 041 21 Košice, Slovakia)

  • Tomáš Musil

    (Faculty of Aeronautics, Technical University of Košice, Rampová 7, 041 21 Košice, Slovakia)

  • Rastislav Jurč

    (Faculty of Aeronautics, Technical University of Košice, Rampová 7, 041 21 Košice, Slovakia)

Abstract

The coronavirus disease has influenced almost all of our everyday activities. Traveling and transportation have been influenced significantly and there is no doubt that air transportation has been restricted and therefore reduced considerably. It is predicted that the change back to pre-pandemic conditions will take several years, and so it is a reasonable assumption that disinfectants will be used more frequently for a long time. The presented article initially deals with the possible impacts of the pandemic on aircraft infrastructure—namely, on the influence of disinfectants on the rubber materials used, for example, in conveyor belts. The proposed methodology is based on the Weibull analysis for conveyor belt lifetime prediction regarding the impact of disinfectants. The Weibull distribution is a continuous probability distribution that can be applied as a theoretical model for statistical data processing. It was named after Weibull, who suggested shape, scale, and location parameters that made the distribution meaningful and useful. Currently, this distribution is applied in many areas, such as biology, economics, and hydrology. In engineering applications, it can be used for reliability and survival analysis. It is used mainly in cases where failure time is dependent on the operating hours, cycles, or age of the component. In the reliability area, it can be used, for example, to predict the lifetime or failure time of a component. To show the consequences of material changes due to the use of disinfectants, this article also presents a CAE (Computer Aided Engineering) analysis that was used for the evaluation of other hyperelastic material characteristics. This research is based on the results of experimental measurements, during which the influence of the types of disinfectant commonly used for the elimination of the coronavirus disease on airport conveyor belt rubber segments was tested. From the performed analysis, it was found that the influence of disinfectants on the material characteristics, including material hardness, elasticity, and static and dynamic loading, could be significant. Therefore, the probability of mechanical damage to the rubber part of the conveyor belt becomes higher, and time intervals for the maintenance or repair of airport conveyor belts should be considered.

Suggested Citation

  • Katarína Draganová & Karol Semrád & Monika Blišťanová & Tomáš Musil & Rastislav Jurč, 2021. "Influence of Disinfectants on Airport Conveyor Belts," Sustainability, MDPI, vol. 13(19), pages 1-13, September.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:19:p:10842-:d:646538
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/19/10842/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/19/10842/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Liu, Xiangwei & He, Daijie & Lodewijks, Gabriel & Pang, Yusong & Mei, Jie, 2019. "Integrated decision making for predictive maintenance of belt conveyor systems," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 347-351.
    2. Silahli, Baykar & Dingec, Kemal Dincer & Cifter, Atilla & Aydin, Nezir, 2021. "Portfolio value-at-risk with two-sided Weibull distribution: Evidence from cryptocurrency markets," Finance Research Letters, Elsevier, vol. 38(C).
    3. Hadi Saboori & Ghobad Barmalzan & Seyyed Masih Ayat, 2020. "Generalized Modified Inverse Weibull Distribution: Its Properties and Applications," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 82(2), pages 247-269, November.
    4. S. M. Mizanur Rahman & Junbeum Kim & Bertrand Laratte, 2021. "Disruption in Circularity? Impact analysis of COVID-19 on ship recycling using Weibull tonnage estimation and scenario analysis method," Post-Print hal-02946987, HAL.
    5. Aliyu Ismail Ishaq & Alfred Adewole Abiodun, 2020. "The Maxwell–Weibull Distribution in Modeling Lifetime Datasets," Annals of Data Science, Springer, vol. 7(4), pages 639-662, December.
    6. Kam, Olle Michel & Noël, Stéphane & Ramenah, Harry & Kasser, Pierre & Tanougast, Camel, 2021. "Comparative Weibull distribution methods for reliable global solar irradiance assessment in France areas," Renewable Energy, Elsevier, vol. 165(P1), pages 194-210.
    7. Zhang, Cai Wen, 2021. "Weibull parameter estimation and reliability analysis with zero-failure data from high-quality products," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    8. Višnja Jurić & Tomasz J. Kozubowski & Mihael Perman, 2020. "An asymmetric multivariate weibull distribution," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 49(18), pages 4394-4412, September.
    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. Yang Han & Guoqi Han & Dongqiao Li & Junfeng Duan & Yewen Yan, 2023. "Numerical Simulation of Assembly Process and Sealing Reliability of T-Rubber Gasket Pipe Joints," Sustainability, MDPI, vol. 15(6), pages 1-13, March.

    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. Chen, Chuanhai & Li, Bowen & Guo, Jinyan & Liu, Zhifeng & Qi, Baobao & Hua, Chunlei, 2022. "Bearing life prediction method based on the improved FIDES reliability model," Reliability Engineering and System Safety, Elsevier, vol. 227(C).
    2. Zhang Yu & Muhammad Umar & S. Abdul Rehman, 2022. "Adoption of technological innovation and recycling practices in automobile sector: under the Covid-19 pandemic," Operations Management Research, Springer, vol. 15(1), pages 298-306, June.
    3. Syed Abdul Rehman Khan & Pablo Ponce & George Thomas & Zhang Yu & Mohammad Saad Al-Ahmadi & Muhammad Tanveer, 2021. "Digital Technologies, Circular Economy Practices and Environmental Policies in the Era of COVID-19," Sustainability, MDPI, vol. 13(22), pages 1-14, November.
    4. Baibhaw Kumar & Gábor Szepesi & Zsolt Čonka & Michal Kolcun & Zsolt Péter & László Berényi & Zoltán Szamosi, 2021. "Trendline Assessment of Solar Energy Potential in Hungary and Current Scenario of Renewable Energy in the Visegrád Countries for Future Sustainability," Sustainability, MDPI, vol. 13(10), pages 1-16, May.
    5. Siti Fatihah Salleh & Ahmad Abubakar Suleiman & Hanita Daud & Mahmod Othman & Rajalingam Sokkalingam & Karl Wagner, 2023. "Tropically Adapted Passive Building: A Descriptive-Analytical Approach Using Multiple Linear Regression and Probability Models to Predict Indoor Temperature," Sustainability, MDPI, vol. 15(18), pages 1-25, September.
    6. Ahmed, Umair & Carpitella, Silvia & Certa, Antonella, 2021. "An integrated methodological approach for optimising complex systems subjected to predictive maintenance," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    7. Ryszard Błażej & Leszek Jurdziak & Agata Kirjanów-Błażej & Mirosław Bajda & Dominika Olchówka & Aleksandra Rzeszowska, 2022. "Profitability of Conveyor Belt Refurbishment and Diagnostics in the Light of the Circular Economy and the Full and Effective Use of Resources," Energies, MDPI, vol. 15(20), pages 1-15, October.
    8. Khanahmadi, Abbas & Ghaffarpour, Reza, 2022. "A cost-effective and emission-Aware hybrid system considering uncertainty: A case study in a remote area," Renewable Energy, Elsevier, vol. 201(P1), pages 977-992.
    9. Jiang, Renyan & Qi, Faqun & Cao, Yu, 2023. "Relation between aging intensity function and WPP plot and its application in reliability modelling," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    10. Chang, Ping-Chen, 2022. "MC-based simulation approach for two-terminal multi-state network reliability evaluation without knowing d-MCs," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    11. Chowdhury, Priyabrata & Paul, Sanjoy Kumar & Kaisar, Shahriar & Moktadir, Md. Abdul, 2021. "COVID-19 pandemic related supply chain studies: A systematic review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    12. Agnieszka Szmelter-Jarosz & Javid Ghahremani-Nahr & Hamed Nozari, 2021. "A Neutrosophic Fuzzy Optimisation Model for Optimal Sustainable Closed-Loop Supply Chain Network during COVID-19," JRFM, MDPI, vol. 14(11), pages 1-22, November.
    13. Abdulaziz S. Alghamdi & M. M. Abd El-Raouf, 2023. "A New Alpha Power Cosine-Weibull Model with Applications to Hydrological and Engineering Data," Mathematics, MDPI, vol. 11(3), pages 1-25, January.
    14. Shiyuan E & Yanzhong Wang & Bin Xie & Fengxia Lu, 2023. "A Reliability-Based Robust Design Optimization Method for Rolling Bearing Fatigue under Cyclic Load Spectrum," Mathematics, MDPI, vol. 11(13), pages 1-16, June.
    15. Haiping Ren & Xue Hu, 2023. "Bayesian Estimations of Shannon Entropy and Rényi Entropy of Inverse Weibull Distribution," Mathematics, MDPI, vol. 11(11), pages 1-16, May.
    16. Zhou, Hang & Lopes Genez, Thiago Augusto & Brintrup, Alexandra & Parlikad, Ajith Kumar, 2022. "A hybrid-learning decomposition algorithm for competing risk identification within fleets of complex engineering systems," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    17. Asim Kumar Sarker & Abul Kalam Azad & Mohammad G. Rasul & Arun Teja Doppalapudi, 2023. "Prospect of Green Hydrogen Generation from Hybrid Renewable Energy Sources: A Review," Energies, MDPI, vol. 16(3), pages 1-17, February.
    18. Karol Semrád & Katarína Draganová, 2022. "Non-Destructive Testing of Pipe Conveyor Belts Using Glass-Coated Magnetic Microwires," Sustainability, MDPI, vol. 14(14), pages 1-15, July.
    19. Chang, Ping-Chen & Huang, Ding-Hsiang & Lin, Yi-Kuei & Nguyen, Thi-Phuong, 2021. "Reliability and maintenance models for a time-related multi-state flow network via d-MC approach," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    20. Sylwester Kaczmarzewski & Piotr Olczak & Maciej Sołtysik, 2021. "The Impact of Electricity Consumption Profile in Underground Mines to Cooperate with RES," Energies, MDPI, vol. 14(18), pages 1-20, September.

    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:jsusta:v:13:y:2021:i:19:p:10842-:d:646538. 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.