Abstract： This paper focused on complex quayside container crane systems consisting of different machines with various degradation processes. An interactive dynamic opportunistic maintenance policy was proposed for supporting the intelligent maintenance decisionmaking. Based on maintenance effects and environmental condition, a hybrid hazard rate recursion evolution was developed for individual machines. Besides, a multiattribute maintenance model utilizing the multiple attribute value theory and dynamic cycles was presented to optimize the maintenance schedule for each single machine. Furthermore, considering the series system structure, the combining interval timeline (CIT) programming was applied to combine related predictive maintenance actions by using the maintenance opportunities in the system level. The results of system maintenance schedules prove that the proposed methodology can effectively reduce the total maintenance cost and decrease the decisionmaking complexity.