Statistical modelling of the service life prediction of painted surfaces

Abstract

Service life prediction assumes a primary role as it allows a more rational use of construction elements. This constitutes a useful tool in the definition of preventive maintenance plans providing an increase in performance. The main objective of this research is the development of a statistical methodology for the service life prediction of external painted surfaces. This research is based on field data collected via a survey of the state of deterioration of in-service buildings. The degradation is defined by a number of factors that together contribute to the deterioration of painted surfaces thus ending their service life. In this study a mathematical model was defined using a multiple linear regression analysis and this enables the coating's deterioration over time to be expressed as a function of various degradation factors. 220 painted coatings were inspected in 160 buildings of varying construction types. Analytical tools were devised to monitor the performance of paint coatings on walls and estimate their service life. This study contributes to the automation of the maintenance of painted facades, allowing a more rational management of the maintenance of buildings, converted into economic and performance gains.

First Publish Online: 19 Jun 2015