As the industry takes its message to lawmakers today during “Railroad Day” on Capitol Hill, the industry is on a roll. Revenue is up 19 percent since 2009 to $80.6 billion, creating 10,000 new directly related jobs and countless other ancillary jobs. Some $21 billion in wages were paid last year alone, a $1 billion increase from the year before.
As a way to magnify direct capital investment in railroad equipment and infrastructure, America’s railroads have been working to use “Big Data” to improve efficiency and capacity. When we pull the “Big Data,” crunch the numbers, and apply the results to real-world operations, the outcomes are flexible, efficient solutions to the network and machinery.
What does big data and the Industrial Internet mean for railroads? With smart new interconnected networks, shippers will have even greater contact with their carloads as goods move across the country. Shipping containers are now integrated with the machines that move them, and the collaboration already saves time and energy. Railroads are an incredibly fuel-efficient mode of transportation. Today trains can move one ton of goods about 500 miles on a single gallon of fuel. According to the Association of American Railroads, on an average, railroads are four times more fuel efficient than trucks. Tack on the effect of cutting-edge technologies, and annual fuel costs can be cut by an additional 10 percent.
The key challenge, of course, is how to handle the highly complex scale, volume, velocity, security, and regulations associated with industrial data. Things get complicated in a hurry. Crews are scheduled, as are locomotives, freight cars, tracks, and terminals, but once these all get rolling, the slightest snag in the system—bad weather, breakdowns, unscheduled maintenance, etc.—can unravel even the best-laid plans. These brilliant machines of the Industrial Internet evaluate tradeoffs, optimize decisions, and apply lessons learned, and then provide the appropriate information to other machines, companies, and people for decision making.
For the railroad sector, data-based innovation is critical for an industry that owns, maintains, and upgrades its own infrastructure to the tune of $20 billion a year. Now compare that to the $40 billion a year in federal subsidies that goes to the nation’s highways. Current system inefficiencies result in higher operating costs to the railroads. Improving the operating ratio by just 1 percent would result in a savings of $800 million to Class 1 railroads.
Sophisticated software can collect and analyze locomotive performance through automated diagnostics and root cause analysis that provides alerts to potential trouble areas well before a breakdown happens. Such proactive maintenance is crucial as even minor delays on a rail line can wreck havoc on schedules and deliveries up and down the line. The resulting improved reliability and availability equates to bottom line savings and decreased life cycle costs.
As our nation’s reliance on rail continues to grow, so will the need for increased capacity and efficiency on the nation’s rail network. To meet this imperative, we need sustainable policies that support continued railroad investment in their own infrastructure.
GE supports balanced policies that enable more investment, maintaining the system, and enhancing safety and efficiency. And as we pursue these goals, we’ll also be introducing more innovation through data and analytics. With a continually evolving and vital rail sector, the real winners will be America’s producers and consumers.
Peter Thomas is commercial leader, RailConnect 360 for GE Transportation.
Top image credit: Flickr