Print Email Facebook Twitter Resilience-based approach to maintenance asset and operational cost planning Title Resilience-based approach to maintenance asset and operational cost planning Author Sun, Hao (China University of Petroleum (East China)) Yang, M. (TU Delft Safety and Security Science) Wang, Haiqing (China University of Petroleum (East China)) Date 2022 Abstract Reliability-based and risk-based methods for directing maintenance activities play a critical role in ensuring system safety and reducing unnecessary downtime. Those methods focus on preventive maintenance to avoid component failures and are applicable before unexpected disruptions occur. However, when disruptions are unavoidable, more attention should be paid to systems’ recovery from unwanted changes. As a remedy of preventive maintenance, improving system restoration capacity of resilience through optimizing the system's maintenance asset and operational cost is an efficient way to help system restore from disruption conditions within an optimal cost. In this paper, a resilience-based approach is proposed to optimize maintenance asset and operational cost. A novel resilience metric is developed and utilized to quantify system resilience under various restoration capacities. The minimal acceptable resilience level (MARL) and maximal acceptable restoration time (MART) are proposed to determine the optimal maintenance cost. The proposed approach is applied to the Chevron Richmond refinery crude unit and its upstream process. The results show that it can help practitioners identify the optimal cost to ensure a system is resilient to respond to uncertain disruptions and provide a dynamic resilience profile to support decision-making. Subject Cost optimizationMaintenanceProcess systemsResilienceRestoration To reference this document use: http://resolver.tudelft.nl/uuid:bde655ee-4d45-45e4-a976-4fc948f67c9a DOI https://doi.org/10.1016/j.psep.2022.05.002 ISSN 0957-5820 Source Process Safety and Environmental Protection, 162, 987-997 Part of collection Institutional Repository Document type journal article Rights © 2022 Hao Sun, M. Yang, Haiqing Wang Files PDF 1_s2.0_S0957582022003949_main.pdf 5.54 MB Close viewer /islandora/object/uuid:bde655ee-4d45-45e4-a976-4fc948f67c9a/datastream/OBJ/view