Universitat Politècnica de Catalunya
Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Projectes i de la Construcció
Universitat Politècnica de Catalunya. GRIC - Grup de Recerca i Innovació de la Construcció
2017
The performance of a building decreases with time and this process is accelerated if proper maintenance is not carried out. This paper presents a discussion about the importance of predictive maintenance actions to enhance the condition of existing buildings. An approach based on Bayesian networks (BN) is proposed to predict the condition of a building. The proposed approach consists of a conceptual and generic model, including the factors with more influence in the condition of a building, which were identified by a literature review. The relationships between these factors and a discussion about the application of this model in maintenance decision-making are provided.
Peer Reviewed
Postprint (published version)
Conference report
Anglès
Àrees temàtiques de la UPC::Edificació::Manteniment d'edificis; Buildings--Maintenance; Bayesian statistical decision theory; Building performance; Decision-making; Predictive maintenance; Edificis -- Manteniment i reparació; Estadística bayesiana
Heriot-Watt University
http://www.lc3-2017.com/uploads/jc3_proceedings_final.pdf
Restricted access - publisher's policy
E-prints [72986]
