Incorporating Predictive Maintenance Best Practices Into Marine Corps Training and Operations

Abstract

The Marine Corps currently utilizes a traditional time-based strategy for ground equipment maintenance, conducting preventative maintenance at specified time intervals and corrective maintenance when failure occurs. In 2020, the Marine Corps initiated the transition from this maintenance strategy to a Condition Based Maintenance Plus (CBM+) strategy, which detects subcomponent anomalies in advance through data analytics so maintenance can be conducted before failure occurs. Hypothetically, CBM+ will generate increased cost-savings, reduce man-hour requirements, and improve operational availability for Marine Corps ground systems. Using a case study methodology, this project highlights best practices within the commercial mining, railroad, and heavy equipment industries by interviewing maintenance professionals and supplementing these discussions with existing literature. We then used a thematic analysis across five themes: organizational structure, asset classification, information technology (IT) infrastructure, data management, and maintenance decision making. By highlighting commonalities across the cases and evaluating best practices, we came to three key conclusions. In the first instance, some of Marine Corps ground systems are not CBM+ compatible. In the second, significant upgrades to existing maintenance infrastructure are necessary. Finally, CBM+ should be used as a decision-making framework to maximize cost-savings and combat readiness.