TI-Analytics monitors Communication Based Train Control (CBTC) underling sub-systems, aggregates data and provides instant visibility on system’s key performance indicators (KPIs) from reliability, availability and maintainability standpoints, converts data into information for comprehensive root-cause analysis of systematic faults, discovers and monitors indicators leading to vehicles, communication or infrastructure faults for proactive maintenance.

In short, TI-Analytics enables proactive and cost efficient maintenance practices for preventing service disruption.

Operators and maintainers are expected to deliver highly available and efficient operations. Each train is a major investment and must operate to its maximum capability.

A train or infrastructure failure affecting passenger service is inacceptable and costly. Optimising maintenance staff to ensure that preventative measures are performed at the right time, while minimising corrective maintenance, is the balancing act every O&M organisation must stay on top of to control budgets and keep customers satisfied.

TI-Analytics provides the overview and feedback that gives to proactive maintenance managers the visibility needed to determine their current asset performance, to discover leading indicators to system failures, to implement predictive maintenance procedures, and to measure their impact on asset reliability and ownership costs.

Converting data into Information

TI-Analytics stores every meaningful CBTC message or event. The reporting component presents the data in a way that allows operators and maintainers to focus on critical failures, the events leading up to failures, and those that follow. A failure is not always random: often it is systematic. Using TI-Analytics reports, the maintainer is able to discover correlations between systematic failures and particular locations, tracks, system parameters, etc. or any of their combinations. As a result, converting CBTC data into visual information leads to a shorter maintenance cycle and a better understanding of fault causality.

Monitoring indicators leading to system failures for preventing service disruption

Preventing service disruption by recognizing and monitoring indicators leading to critical faults is a key business function of TI-Analytics analysis and alerting features. TI-Analytics builds an analytical database of all CBTC historic events. Maintainers can explore this database by conducting root-cause analyses through interactive drill-down reports and through the ‘decomposition tree’ explorer. As a result, the maintainer can now understand indicators that lead to these failures, define rules for monitoring of these indicators, and configure corresponding alerts for proactive maintenance.

Knowledge discovery based on interactive and statistical analyses of empirical CBTC data

Often, system irregularities, such as vehicle faults, overspeed, train emergency break operation, and other negative operational issues are caused by a combination of system parameters and external factors. TI-Analytics data mining component reveals hidden patterns and empirical correlations between negative events and a combination of different parameters. The resulting discovery of knowledge leads to improved system reliability and increased efficiency of maintenance practices.

Automated fleet mileage calculation

TI-Analytics continuously calculates and reports accumulated mileage in real time for all trains. This significantly reduces operating costs by eliminating the need for daily, manual odometer reading. By interfacing directly to maintenance management systems, maintainer could automate generation of work orders based on vehicle’s accumulative mileage.

TI-Analytics is a business intelligence platform for discovering leading indicators to service disruption and for sending alerts for predictive fleet maintenance, wayside, guideway and infrastructure maintenance. It also includes components for fleet mileage calculation and interactive reports that reveal the cause of systematic faults.

TI-Analytics provides a return on investment within 1 to 2 years for a typical 20 train operation. Lines with larger fleets can expect a significantly improved return on investment. Lines currently operating with minimal automation will see an instant return within the first year.

Invest today in the long-term savings of TI-Analytics and see your assets deliver customer satisfaction tomorrow