SMRT Trains Ltd

The first rail operator in Singapore, SMRT Trains (SMRT) operates and maintains over 282 kilometers of rail track in the island country. With an average daily ridership of over 2 million people in 2020, SMRT needed a method to keep the tracks in good condition to avoid delays. System reliability is measured using mean kilometers between failure (MKBF), where a failure is defined as a service delay of more than five minutes. So, to improve their reliability, SMRT set a target of 1 million MKBF for all their lines. This target is the equivalent of traveling over the entire network thousands of times before seeing a service delay of five minutes or more. However, they were relying on intensive, time-consuming, and manual maintenance planning using tens of millions of data points per year across separate data silos.

SMRT wanted to upgrade their legacy processes and improve its maintenance strategy so that the tracks stayed in a good serviceable state. They sought to create a data repository that would house all their data in a single location to improve decision-making as well as be available 24/7 so that the day and night shift engineers could easily access it. To enable engineers to make optimized decisions using all relevant data, SMRT used Bentley’s AssetWise Linear Analytics as the basis of their predictive decision support system (PDSS). With the PDSS, engineers can visualize multiple datasets in one view to see different track subsystems, enabling more in-depth engineering analysis. The AssetWise-based platform automatically pulled four years of SMRT’s data from asset configuration information, inspection records, and operating data. With historic information retained, engineers can review the sequence of events leading to the current asset condition. Additionally, because the PDSS is a cloud-based service, new users can receive secure access without needing to install any software on their local IT infrastructure. With automatic data processing, analysis, and visualization, users gain greater insight from the data for improved asset condition analysis and hotspot determination.

As of August 2019, SMRT achieved 1 million MKBF across all their rail lines. Their PDSS enables them to overlay multiple data sources within seconds rather than hours. Data correlation is twice as fast as the existing manual method, while the design allows for easy access to data, significantly streamlining multiple analyses. The table is updated every day and easily accessible via the web. With prioritization implementation, they managed to cut down hundreds of manual planning hours and save about 20 maintenance train deployments annually. Their engineers have a better idea of the work conditions, allowing them to prepare for the necessary repair work in advance to save time on the site. Moving forward, SMRT plans to continuously improve their maintenance efficiency and effectiveness.

• SMRT wanted to upgrade their processes and improve its maintenance strategy so that the tracks stayed in a good serviceable state.
• They used Bentley’s AssetWise Linear Analytics as the basis of their predictive decision support system.
• As of August 2019, SMRT achieved 1 million MKBF across their rail lines.

“By providing a holistic assessment of the whole network’s asset condition, [the] PDSS helps engineers manage long-term maintenance planning and both anticipate and justify the need for asset renewal. All of these capabilities enable engineers to move further towards an optimized condition-based maintenance regime, increasing maintenance efficiency and asset reliability.”