A dynamic multi-criteria decision-making model for the maintenance planning of reinforced concrete structures. (January 2020)

• Record Type: Journal Article
• Authors: Benítez, Pablo; Rocha, Eugénio; Varum, Humberto; Rodrigues, Fernanda
• Is Part Of: Journal of building engineering. Volume 27(2020)
• Publication Date: 2020-01
• Subjects: Decision-Making -- Inspections -- Corrosion -- Repair -- Concrete structures -- Analytic hierarchy process; Building -- Periodicals; 690.05
• DOI: 10.1016/j.jobe.2019.100971
• Languages: English
• ISSNs: 2352-7102

Abstract

Abstract: Decision-making is essential in buildings management process playing a decisive role in the maintenance planning design. Multi-Criteria Decision Making (MCDM) methods can be applied as a support tool to fulfil a set of requirements that arise during the scheduling of maintenance activities of these structures. The Analytic Hierarchy Process (AHP) is a broadly recognised methodology applied to model subjectively decision problems based on multi attributes analysis. This paper applies the AHP method under an objective approach, where the weight assignments are stochastically calculated instead of defining it based on the judgement of experts. The main objective of this study is to propose a dynamic decision model based on AHP for the maintenance planning of reinforced concrete structures under corrosion risk. This methodology provides the best maintenance alternative (inspection/repair) to be performed in these structures for a given intervention time. The best solution for the intervention is chosen regarding the Global Priority Vector of the final pairwise comparison matrix. After an illustrative application, the new dynamic decision model developed proven be a helpful tool for decisions-making regarding the most suitable intervention alternative within the maintenance planning of these structures. Highlights: Stochastic indexes are proposed to address uncertainties of the degradation process. The model proposed has proven to be a useful support tool for the maintenance planning. The model generates a ranking of intervention alternatives for structures with corrosion degradation.