Towards smarter infrastructure investment: A comprehensive data-driven decision support model for asset lifecycle optimisation using stochastic dynamic programming

Equipment renewal and replacement strategy as well as smart capital investment is a vital focus in engineering asset management, particularly for water utilities aiming to improve asset reliability, water quality, service continuity and affordability. This study presents a novel decision support model that integrates whole-life costing principles across all asset lifecycle phases—from capital delivery and daily operations to long-term maintenance. The proposed model uniquely combines asset degradation and failure patterns, operating and maintenance costs, and the impact of technological advancements to provide a holistic and comprehensive asset management decision-making tool. These dimensions are jointly analysed using a hybrid approach that combines optimisation with stochastic dynamic programming, allowing for the determination of optimal asset renewal and replacement timing. The model’s performance was validated using historical data from eight critical wastewater pump stations within a township’s sewerage network. This was performed by comparing the model’s cost-saving results to those achieved by the water utility’s current strategy. Results revealed that the proposed model achieved an average cost saving of 12%, demonstrating its effectiveness in supporting sustainable and cost-efficient asset renewal decisions.