A stochastic approach to optimising façade maintenance in healthcare buildings

Purpose Developing effective maintenance strategies is a major challenge for healthcare facility managers to ensure the ongoing operation of buildings. The aim of this research was to model the degradation of the façades of Healthcare Buildings, determining the best maintenance decision for new and in-use buildings based on their expected value over the service life. Design/methodology/approach A Markov chain-based approach was developed to model the degradation of painted cement-rendered façade, in combination with Monte Carlo simulations to reduce the uncertainty associated with maintenance cost to estimate the expected value of cladding maintenance through a Decision tree. Findings The results suggest that, under the conditions of the study, the cladding should be replaced between years 17 and 19 for 92.67% of the simulated scenarios, being the most cost-effective at year 18. In addition, year 8 of a cladding is the optimal year to repair it, leading to an increase in their service life by 18.70. The model also demonstrated the influence of variability in maintenance costs on intervention planning and service life optimisation. Originality/value This research proposes a data-driven probabilistic framework that enables degradation modelling and economic assessment for maintenance decision-making in Healthcare Buildings. Unlike conventional approaches, which rely on fixed assumptions about service life or expert judgement, the proposed methodology enables the optimisation of repair strategies under variable maintenance cost scenarios.