As the bandwidth of cellular links rises, off-highway suppliers and users alike are striving to get even more functionality. That’s especially true with one of the common telematic features, gathering diagnostic information.
There can be huge benefits when diagnostic data turns into prognostics, alerting operators that a component or system is nearing its failure points. Prognostics is already common for fluids—Allison Transmissions includes it on every automatic transmission.
However, prognostics is more of a challenge for mechanical parts. It’s no simple task to analyze vibration, temperature, and other parameters and determine that a field failure is imminent unless a service stop is scheduled.
Technologists have to understand all sorts of subtleties to predict failures without calling vehicles in for unnecessary repairs. That’s a complex task that involves many different engineering and scientific disciplines.
“Decades of work have been dedicated to looking at the mechanics behind failures,” said Denny Stephens, Research Leader, Vehicle System Safety Research & Engineering at Battelle Transportation Operations Research. “We’re looking at the fundamental mechanical causes of wear and looking at cost-effective sensors that monitor the progress of wear until it reaches a threshold where failure is imminent.”
The ability to send more data to maintenance shops is a small portion of the transition from diagnostics to prognostics. Programmers and analysts have to figure out how to best analyze and utilize the huge volumes of information now called big data.
“Having an open house for data collection will not make a wiser person,” said Thilo Koslowski, Vice President for Automotive at Gartner. “When it comes to something like prognostics, figuring out what’s going to happen is still a huge challenge. Big data often brings many more questions before it brings answers.”