Corrective maintenance minimizing expected mission losses in shock exposed multistate production-storage systems

Production-storage systems are often subject to random external shocks such as storm weather and electromagnetic interference. However, most of the existing models failed to take the shock effects into consideration. This paper extends the state of the art by modeling random shocks and optimizing their mitigating corrective maintenance policy (CMP) that defines the condition triggering repair actions to restore the production subsystem to a higher performance level. The CMP can greatly impact the amount of unsupplied product as well as the maintenance and operation costs, all contributing to the expected mission losses (EML). This paper contributes by modeling and optimizing the CMP to minimize the EML. The proposed solution encompasses a new numerical algorithm that evaluates the EML of the considered production-storage system under a given CMP and the genetic algorithm realized for solving the CMP optimization problem. The proposed model is demonstrated using a case study of a multistate power generation system subject to voltage surges due to storm weather. Based on the investigation of effects of several model parameters (shock rate, storage capacity, initial amount of product in the storage, cost of unsupplied product) on the EML and optimization solutions, useful and insightful management recommendations are provided.