North America - Combining Big Data Analytics With Remote Monitoring, advancing safe and efficient rail operations continues to be a primary focus of North American freight railroad operations.
 
What is particularly exciting right now is that the data available to railroads, both in its detail and volume, enables them to manage their operations in ways that were not possible before.
 
Monitoring and maintaining the health of the industry's rolling assets is a key enabler of this progress, which is why railroads continue to invest in an array of devices and processes.
 
These include condition-based detection systems, data warehouse, and Big Data systems that support data mining and advanced analytics, all to support the health of the freight car fleet.
 
Today, the industry has proactive, condition-based, monitoring that helps maintain a safe and efficient rail network.
 
With more sophisticated wayside detection systems, tracking of critical railcar components, better operating practices, and advanced analytics, railroads are recognizing potential mechanical issues earlier than ever.
 
These systems generate data available in detail and quantities that were unimaginable just 10 years ago.
 
The railroads are leveraging this data to identify potential mechanical problems earlier and take proactive measures that prevent those problems from causing track damage or train delays.
 
Plus, the railroads' continued investment in detection systems, the ongoing development of new detector types, improvements in the quality of field inspections, and new analytics has made it possible to identify potential railcar problems sooner and before interruption in service occurs.
 
With more than 1.5 million cars in service today, these improvements decrease costs and make the rail network more reliable.
 
One of the primary drivers for the increase in data and the ability to use it is the efforts railroads have made to share data with each other, and the car owner and car repair community.
 
An example is the cooperative, industry-wide, program coordinated through the Association of American Railroads (AAR) known as the Asset Health Strategic Initiative (AHSI).
 
Launched in 2012, AHSI encompasses the entire rolling stock health cycle, which incorporates prevention, detection, planning, movement, repair, and interline settlement.
 
The AAR, Railinc, and Transportation Technology Center Inc. (TTCI) are helping advance this program with the railroads.
 
The goals of AHSI are:

• Enable industry-wide improvements in safety, velocity, and capacity;
   
  
• Enable more-reliable service through more-effective asset health management;
   
  
• Optimize capital investment in track, yards, and equipment required to handle increased rail volume;
   
  
• Support safe and cost-effective operations.

Through this program, advanced railroad detection systems using image, laser, acoustics, and impact sensors are identifying potential problems with components such as wheels, axles, bearings, and brakes.
 
Advanced analytical programs flag suspect cars that can be removed from service and fixed before issues arise.
 
This program is helping the industry improve on a record of safety and efficiency that is already at historically high levels.
 
Each railroad closely monitors and acts on flags that come from automatic and manual detection systems on their lines.
 
Collectively, they send this data to Railinc's Asset Information Repository (AIR), an aggregated North American database that provides continuous visibility into the health status of freight cars and locomotives.
 
This comprehensive view enables faster identification and resolution of cars that are developing mechanical defects.
 
As an example, when a freight train goes into emergency brake mode, and the train crew is unable to identify a specific car or cars that could have caused the brake application, that event is sent into AIR.
 
The event is stored with other similar events across the industry and tracked over time.
 
The cars in such a train can move across North America, interchanging among railroads, resulting in multiple event reports to the Asset Health Mechanical AIR system.
 
The Asset Health Mechanical algorithms in the system can identify specific cars involved in these events on multiple railroads.
 
Railinc, with its view of unintended emergency brake applications across North America, flags those cars, isolating a specific car or cars that become suspect.
 
Once identified, Railinc notifies the industry so that qualified mechanical shops can inspect the equipment.
 
Cars that are repaired and returned to service will increase velocity by eliminating future issues.
 
This is just one example of how the use and development of analytical programs has been part of a broader strategic focus at the network level to support equipment health.
 
AHSI was made possible by the investment of Class I railroads and their commitment to work together to further safety and efficiency to make a better freight rail network.
 
There are many other systems utilized by the North American rail industry that help advance safe and efficient rail operations, including:
 
The UMLER equipment database provides the foundation for AHSI equipment information. This foundational system is the industry's central electronic resource for critical equipment characteristic data. It is used by railroads, equipment owners, shippers, ports, suppliers, industry consultants, government agencies, and car maintenance facilities for the safe and efficient placement, movement, and interchange of cars. The UMLER system provides secure access to equipment management and reporting tools.
 
The Equipment Health Management System (EHMS) is an application that communicates the condition of equipment and sends alerts to the responsible parties when repairs are needed. In cooperation with TTCI, EHMS scrubs, stores, and distributes data from multiple wayside detectors. These detectors are deployed to identify potential issues to critical components such as wheels, bearings, and trucks while the train is in motion, this gives real-time feedback to host roads. Railroads share this information to eliminate potential issues long before any issue can arise.
 
The AAR Component Tracking Program is a multi-phase, multi-year initiative to create an industry process and related technology tools for capturing railcar equipment component data. Providing rail industry participants with visibility into component health and performance, it tracks individual components as they are applied to specific cars. More component types are being steadily brought into the program like side frames, bolsters, couplers, brake valves, and slack adjusters. The AAR Equipment Health Monitoring Committee and other industry committees guide this effort.
 
Damaged and Defective Car Tracking (DDCT) enables users to update, retrieve, and share information on cars moving to shops. It is an industry collaboration for incident reporting, management of equipment disposition, and repair reporting. DDCT puts reliable data at the disposal of car owners, rail carriers and repair shops, helping them make better and faster decisions about equipment requiring attention.
 
The AAR, Railinc, and TTCI, through AHSI, support the industry's commitment to continuous improvement, and it has yielded significant results.
 
AHSI was built on existing systems including UMLER, EHMS, Component Tracking, and DDCT, along with an increasingly sophisticated array of detectors, to enable a new level of data analytics that supports safe and efficient movement of goods that are critical to the North American economy.
 
Freight rail safety is strong, and getting stronger.
 
Railroad investment to modernize and improve America's freight rail network has significantly contributed to freight rail's strong safety record.
 
In fact, there is a direct correlation between the increase in rail network investments and enhanced safety performance.
 
With record levels of private spending on capital improvements and maintenance over the past five years and more than US$25 billion annually on average, America's privately owned freight railroads are at the forefront of advancing safety.
 
2018 rail safety data continues to show that recent years have been the safest on record.
 
According to recent Federal Railroad Administration data, based on per-million train-miles, since 2009 the train accident rate is down 10 percent, the equipment-caused accident rate is down 11 percent, the track-caused accident rate is down 26 percent, the derailment rate is down 9 percent, and the hazmat accident rate is down 48 percent.
 
North America's railroads never stop looking for ways to improve operations.
 
As technology moves forward, so will the freight railroads.
 
It is an exciting time to work on technology projects in the industry, and we see more excitement to come as more intelligent devices and analytics are applied to the data produced.
 
1.5 Million Cars - 600 Railroads - One Industry Focus
 
Less than a decade ago, things looked quite different in the world of freight car management.
 
A growing rail industry understood that its future success was tied to better management of the burgeoning data stream, and that rapid advances would be required in how data was gathered and processed.
 
Today, the industry is experiencing the benefits of that vision as it conducts operations on nearly 600 North American railroads with some 1.5 million cars.
 
A cross-functional task force of senior representatives from throughout the railroad industry developed a strategy for a multi-year program to address rail network challenges related to asset health.
 
In 2015, the Asset Health Strategy Committee was created by bringing that task force together with participants from each Class I railroad, Amtrak, private car owners, the Association of American Railroads, TTCI, and Railinc.
 
Today, the Asset Health Strategy Committee continues its work to apply information technology solutions and processes to address asset health challenges.
 
This industry-wide focus on continual advancement of safety and efficiency supports a strong railroad network.
 
Chip Summey.