Simulating the impact of varying maintenance interventions on asset performance and spare part provisioning in a multi-echelon replenishment system

In today’s industries, optimal maintenance and spare parts replenishment play a critical role in maximizing the asset’s operational availability. The replenishment strategy is influenced by the maintenance strategy implemented within the organization which may include reactive or pro-active maintenance actions or interventions. The replenishment strategy may also be influenced by component reparability which depends on the condition of the component at failure. Other than component reconditioning, the replenishment strategy may be influenced by a pooling strategy where a multi-echelon network may be adopted. Such multi-echelon replenishment may invariably influence equipment downtimes through shortened replenishment lead times. In the literature, few modeling frameworks consider dependencies between the type of maintenance interventions and the resulting influence on system productivity and part demand within the multi-echelon network. Hence, a discrete event simulation model is proposed for quantifying the influence of varying maintenance interventions on system productivity and part demand. A three-echelon replenishment network is considered which consists of an in-house pool, one partner at a higher echelon, and the original equipment manufacturer at the highest echelon. Two maintenance strategies are further adopted: reactive maintenance and pro-active maintenance. An application case of a critical component failure in a thermal power plant is presented.