An optimal two-dimensional maintenance policy for self-service systems with multi-task demands and subject to competing sudden and deterioration-induced failures

Self-service systems, such as electric vehicle charging piles (EVCPs), are typically deployed without on-site personnel. While frequent maintenance ensures high service revenue, it also leads to significant maintenance setup costs. Therefore, balancing service revenue and maintenance costs is essential for profit maximization. In this paper, we develop a maintenance policy optimization framework to maximize the profit rate of a fleet of self-service systems. First, we propose a maintenance policy that ensures sufficient functional systems while preventing high corrective maintenance costs. Next, we model the fleet's state transition process and its profit rate by characterizing two unique failure-induced demand-and-system interactions: demand switching and stepwise demand arrival rates, where the demands involve multiple tasks and systems are subject to multiple failure modes with non-constant occurrence rates. We develop a Tabu-search algorithm with random exploration to optimize the maintenance policy. Building on this, we investigate the impacts of key model parameters through a case study of thirteen EVCPs in Hong Kong and draw implications for profit maximization.