Every year, more than 73 million passengers travel with Copenhagen metro. The system operates 24/7, making maintenance a great challenge. Intervention schedules on the metro assets are time-based. Most components are checked or replaced when their remaining useful life is still acceptable. Maintenance costs are rising every year and the number of passengers is increasing. Given these trends, the market is gradually demanding more and more solutions regarding the optimization of maintenance activities. Data acquisition and real-time data analysis are gaining popularity, since they contain information about asset health (Condition Monitoring) and can be exploited to understand when interventions should be performed (Predictive Maintenance).