Heuristic optimisation for multi-asset intervention planning in a petrochemical plant

Abstract

Large infrastructure assets commonly require high intervention costs, but the absence of an effective asset management plan can bring about a massive production loss for a company. Hence, managing these assets is considered a daunting task and is even more complicated if these assets operate collectively to produce an output. This paper explores a pragmatic approach to a multi-asset intervention scheduling problem through a case study of a vessel fleet in a petrochemical plant. After the relationship between the asset configuration and the system output is defined, an optimisation model with an objective to jointly minimise cost and risk is developed. Since the calculation of risk profiles across the fleet requires complex non-linear functions, a genetic algorithm is employed to search for an optimal combination of intervention schedules. Compared to the current run-to-failure strategy, the optimal strategy results in a significant reduction in system failure risk and a substantial improvement in long-term fleet conditions while reducing the total cost.