Ongoing developments in information technologies, specifically the ability to capture, store, and analyse large datasets, are creating significant opportunities to improve maintenance. The study explored the move towards predictive and data-driven maintenance within CoMET and Nova metros.
There is a clear trend in metros to move toward one asset information system. Integration of systems can bring benefits such as increased efficiency in management and data consistency. It is found that metros are adopting advanced technology (e.g. mobile devices, automatic monitoring systems) to collect data more efficiently. Collection of more detailed maintenance data and use dedicated staff to manage data are also used at the same time to improve data quality.
In order to acquire sufficient data for analysis, metros have initiated various pilot projects adding sensors to monitor asset condition. The study collected the good practices within metros in terms of data collection, analysis and applications, as well as the tangible benefits of data analysis. With the development of auto-monitoring systems and evolution of ‘big data’ analysis, there is a significant opportunity to unlock new understanding about asset performance and lifecycles.