4.6 Article

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

期刊

SUSTAINABILITY
卷 13, 期 12, 页码 -

出版社

MDPI
DOI: 10.3390/su13126922

关键词

fuzzy system; uncertainty; expert panel; decision-making; timber structure; building

资金

  1. Agencia Nacional de Investigacion y Desarrollo (ANID) of Chile [ANID FONDECYT 11190554, ANID FONDECYT 1201052]

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This study utilizes a digital methodology based on a fuzzy logic model to assist professional expert panels in managing uncertainty during building maintenance decisions. It aims to provide support to experts and minimize human errors in the decision-making process.
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.

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