Interface - The Journal of Wheel/Rail Interaction

TECHNOLOGY

Implementing Wheel/Rail Measurement and Analysis Technology
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Finding the ‘Win-Win”
“We are trying to use technology — especially with ATSI — to find that ‘win-win’ between the railroads and the private car fleet,” said Lisa Stabler, BNSF’s Assistant Vice President for Quality and Reliability Engineering.

Railroads are focusing on situations in which they can provide information that car owners can use to perform maintenance that will enable the car to make it to its next maintenance cycle. Instead of dealing with the “lose-lose” of who is going to fix the WILD-identified wheel, railroads and car owners are looking for the “win-win” associated with identifying wheels that the WILD network has predicted will generate high-impact loadings in the near future, and replacing them while the car is in the shop for scheduled maintenance.

BNSF began implementing various wayside technologies in part to reduce the number of mechanical-caused derailments. One derailment that occurred in 2000 played a significant role in the development of BNSF’s widespread wayside detection systems. This low rail rollover derailment was important because it occurred 241 miles beyond an experimental truck-performance detector (TPD) that the train had recently passed. Data from the TPD showed higher L/V forces at the end of the train, where the derailment began. We asked ourselves, Stabler said, if we could have prevented this derailment if the TPD had been in a production rather than a research environment.

Along the way to answering that question, BNSF’s wayside detector network has grown from its initial network of six stand-alone detectors, using two different technologies, to 72 stand-alone detectors, using 12 different technologies. (BNSF also employs a network of 763 warm-bearing detectors.)

Still, competing for resources to establish and expand effective wayside measurement and monitoring programs is an ongoing challenge. Showing management some of the data or pictures identified by detector systems that otherwise would have caused a derailment or service interruption is a good way to get management’s support, Stabler said. One you obtain that support, she said, “you'd better be able to show results.”

That’s why BNSF and the Six Sigma group, which Stabler leads, focus on “validation and quantification” when selecting detector systems. The first thing we do after procuring a detector is determine that it can demonstrate an acceptable R&R (repeatable and reproducible) gauge, Stabler said. After we've demonstrated that it's repeatable and reproducible, we make sure that that it actually does what it’s supposed to do. Before we call it “good,” the car inspector — the person who's going to bad-order the car — has to agree that the detector works. “Field concurrence is critical,” she said.

Dataflow is another critical aspect of wayside detection technology in that railways have begun making decisions about whether a car that is flagged for maintenance must be set out immediately or if it can be bad-ordered and sent to the next mechanical repair facility. This, along with the associated repair work and billing, become part of the car-repair history system.

In the end, it all comes down to dollars. “While we never put a price on safety, we understand that there is a cost associated with derailments,” Stabler said. “We’re all about showing that the money spent on wayside detector technology is generating a return and that we're spending BNSF's money wisely.”

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