For years, analytics specialist Teradata has been helping companies like Union Pacific Railroad make sense of sensor data and to integrate that data with its business processes. But that was just the tip of the iceberg. Chad Meley, vice president of Marketing at Teradata, says today's internet of things (IoT) innovations are poised to rewrite the playbook in manufacturing, transportation, mining, energy and utilities.
"We really see IoT being at a tipping point," Meley says.
And Teradata plans to leverage its experience with companies like Union Pacific to help others make the leap. The company today announced four new services — combinations of technology-agnostic intellectual property and professional consulting services — aimed squarely at helping organizations transform sensor data streams into revenue streams.
The 154-year-old Union Pacific Railroad company is the largest railroad network in the U.S., operating 8,500 locomotives hauling freight over 32,100 route-miles of track in 23 states. With that many trains running over that much track, derailments are more or less inevitable. They can cost between $20 million and $40 million in damages.
20 million sensor readings on track
For more than a decade, Teradata has helped Union Pacific equip sensors that listen to the sounds a train's wheels make going over the tracks. Other sensors measure the temperature of wheels' bearings. The sensors deliver more than 20 million sensor readings daily.
"They could detect an imminent problem," Meley says. "Maybe a wheel exceeded a threshold in terms of heat. They could determine that in the next hour, it's going to derail."
Those sorts of warnings reduced derailments, Meley says, but didn't eliminate them entirely. And with only about an hour of lead time, the company was still losing a massive amount of revenue every time a train was pulled. Even a delay of just a couple of hours could have repercussions for customer commitments up and down the line.
"When your predictive models are trying to guess something immediately before it happens, it's not going to be the best model," Meley says. "You're still going to have derailments."
Modern predictive analytics can ingest and process the streaming data much more rapidly and efficiently. Meley says Union Pacific can now predict a derailment with a high degree of confidence more than a week out, which has cut bearing-related derailments by 75 percent and allowed it to adjust maintenance schedules to reduce maintenance-related delays.
Riding sensors to profitability
In Spain, Teradata has helped Siemens deliver high-speed trains that have made the route between Madrid and Barcelona hyper-reliable. Renfe, the Spanish national railway company, was under pressure to increase profitability on its Alta Velocidad Espanola (AVE) high-speed rail between the two cities.
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