IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i12p6922-d578033.html
   My bibliography  Save this article

Expert Panel, Preventive Maintenance of Heritage Buildings and Fuzzy Logic System: An Application in Valdivia, Chile

Author

Listed:
  • Manuel Carpio

    (Department of Construction Engineering and Management, School of Engineering, Pontificia Universidad Católica de Chile, Avenida Vicuña Mackenna 4860, Santiago 7820436, Chile
    UC Energy Research Center, Pontificia Universidad Católica de Chile, Avenida Vicuña Mackenna 4860, Santiago 7820436, Chile)

  • Andrés J. Prieto

    (Department of Construction Engineering and Management, School of Engineering, Pontificia Universidad Católica de Chile, Avenida Vicuña Mackenna 4860, Santiago 7820436, Chile)

Abstract

The maintenance of buildings is a highly complex decision process, which is generally due to professional experts having to consider several arduous evaluations, especially regarding uncertainty related to why, when and how to intervene. This study concerns the analysis of the uncertainty associated with professional experts’ surveys during the decision-making process during building maintenance. For this purpose, a case study of a timber-structure building was examined. An expert panel of 66 professionals with expertise in construction engineering carried out a systematic and automated evaluation. This kind of digital method is capable of managing the uncertainty associated with the evaluation processes by different specialists. Experts can evaluate various nuances and approximations in the model’s input parameters. The fuzzy model helps to harmonize the results since minor variations in the evaluation of the input parameters do not generate a large dispersion over the model’s output variable. The novelty of this study concerns the application of a digital methodology based on a fuzzy logic model to assist a professional expert panel in different areas—architecture, engineering and construction. This study is oriented through an artificial intelligence based method applied by specialists to set intervention priorities, support maintenance management of the examined building and minimise human error during data collection and uncertainty related to making decisions. The lessons learned from the results obtained in this study promote the use of this kind of digital tool to manage the uncertainty associated with in-situ visual inspections.

Suggested Citation

  • Manuel Carpio & Andrés J. Prieto, 2021. "Expert Panel, Preventive Maintenance of Heritage Buildings and Fuzzy Logic System: An Application in Valdivia, Chile," Sustainability, MDPI, vol. 13(12), pages 1-15, June.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:12:p:6922-:d:578033
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/12/6922/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/12/6922/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Simon P. Philbin, 2021. "Driving Sustainability through Engineering Management and Systems Engineering," Sustainability, MDPI, vol. 13(12), pages 1-7, June.
    2. Rengarajan, Srinath & Moser, Roger & Narayanamurthy, Gopalakrishnan, 2021. "Strategy tools in dynamic environments – An expert-panel study," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    3. Andrés José Prieto & Juan Manuel Macías-Bernal & Ana Silva & Pilar Ortiz, 2019. "Fuzzy Decision-Support System for Safeguarding Tangible and Intangible Cultural Heritage," Sustainability, MDPI, vol. 11(14), pages 1-12, July.
    4. Liv Langfeldt, 2004. "Expert panels evaluating research: decision-making and sources of bias," Research Evaluation, Oxford University Press, vol. 13(1), pages 51-62, April.
    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. Andrew Dustan & Stanislao Maldonado & Juan Manuel Hernandez-Agramonte, 2018. "Motivating bureaucrats with non-monetary incentives when state capacity is weak: Evidence from large-scale field experiments in Peru," Working Papers 136, Peruvian Economic Association.
    2. Wei Wang & Xin Luo & Chongmei Zhang & Jiahao Song & Dingde Xu, 2021. "Can Land Transfer Alleviate the Poverty of the Elderly? Evidence from Rural China," IJERPH, MDPI, vol. 18(21), pages 1-15, October.
    3. Sheheryar Banuri & Stefan Dercon & Varun Gauri, 2019. "Biased Policy Professionals," The World Bank Economic Review, World Bank, vol. 33(2), pages 310-327.
    4. Rengarajan, Srinath & Narayanamurthy, Gopalakrishnan & Moser, Roger & Pereira, Vijay, 2022. "Data strategies for global value chains: Hybridization of small and big data in the aftermath of COVID-19," Journal of Business Research, Elsevier, vol. 144(C), pages 776-787.
    5. Rahman, A.I.M. Jakaria & Guns, Raf & Rousseau, Ronald & Engels, Tim C.E., 2015. "Is the expertise of evaluation panels congruent with the research interests of the research groups: A quantitative approach based on barycenters," Journal of Informetrics, Elsevier, vol. 9(4), pages 704-721.
    6. Thomas Feliciani & Junwen Luo & Lai Ma & Pablo Lucas & Flaminio Squazzoni & Ana Marušić & Kalpana Shankar, 2019. "A scoping review of simulation models of peer review," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 555-594, October.
    7. Eleonora Di Matteo & Paolo Roma & Santo Zafonte & Umberto Panniello & Lorenzo Abbate, 2021. "Development of a Decision Support System Framework for Cultural Heritage Management," Sustainability, MDPI, vol. 13(13), pages 1-27, June.
    8. Cecilia Haskins, 2021. "Systems Engineering for Sustainable Development Goals," Sustainability, MDPI, vol. 13(18), pages 1-3, September.
    9. Benda, Wim G.G. & Engels, Tim C.E., 2011. "The predictive validity of peer review: A selective review of the judgmental forecasting qualities of peers, and implications for innovation in science," International Journal of Forecasting, Elsevier, vol. 27(1), pages 166-182.
    10. Doyeon Lee & Keunhwan Kim, 2022. "Public R&D Projects-Based Investment and Collaboration Framework for an Overarching South Korean National Strategy of Personalized Medicine," IJERPH, MDPI, vol. 19(3), pages 1-25, January.
    11. Peter van den Besselaar & Ulf Sandström & Hélène Schiffbaenker, 2018. "Studying grant decision-making: a linguistic analysis of review reports," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 313-329, October.
    12. Andrea Bonaccorsi & Nicola Melluso & Francesco Alessandro Massucci, 2022. "Exploring the antecedents of interdisciplinarity at the European Research Council: a topic modeling approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 6961-6991, December.
    13. Andrew Dustan & Juan Manuel Hernandez-Agramonte & Stanislao Maldonado, 2018. "Motivating bureaucrats with non-monetary incentives when state capacity is weak: Evidence from large-scale," Natural Field Experiments 00664, The Field Experiments Website.
    14. Qi Li & Mei Liu & Jusheng Song & Yu Du & Fei Gao, 2022. "The Risk Map of Cross-Regional Cultural Heritage: From a Perspective of Slow Degradation," Sustainability, MDPI, vol. 14(21), pages 1-24, October.
    15. Jie Chang & Cheng Long & Song Lu & Rui Han, 2022. "Does Government Positively Support the Spatial Distribution of ICH? Evidence of Data from the Yangtze Delta Region of China," Sustainability, MDPI, vol. 15(1), pages 1-17, December.
    16. Giovanna Acampa & Fabrizio Battisti & Mariolina Grasso, 2023. "An Evaluation System to Optimize the Management of Interventions in the Historic Center of Florence World Heritage Site: From Building Preservation to Block Refurbishment," Land, MDPI, vol. 12(4), pages 1-17, March.
    17. A. Gaunand & L. Colinet & P.-B. Joly & M. Matt, 2022. "Counting what really counts? Assessing the political impact of science," The Journal of Technology Transfer, Springer, vol. 47(3), pages 699-721, June.
    18. Benda, Wim G.G. & Engels, Tim C.E., 2011. "The predictive validity of peer review: A selective review of the judgmental forecasting qualities of peers, and implications for innovation in science," International Journal of Forecasting, Elsevier, vol. 27(1), pages 166-182, January.
    19. Pournader, Mehrdokht & Ghaderi, Hadi & Hassanzadegan, Amir & Fahimnia, Behnam, 2021. "Artificial intelligence applications in supply chain management," International Journal of Production Economics, Elsevier, vol. 241(C).
    20. Bouhalleb, Arafet & Tapinos, Efstathios, 2023. "The impact of scenario planning on entrepreneurial orientation," Technological Forecasting and Social Change, Elsevier, vol. 187(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:jsusta:v:13:y:2021:i:12:p:6922-:d:578033. 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.