IBM announced Tuesday that luxury auto manufacturer BMW is expanding its use of IBM big data analytics software to eliminate defects in new models while they are still in the prototype stage.
The key to fixing problems before they get beyond the test track is capturing plenty of data from sensors on prototype vehicles. Just as Formula 1 race cars are now fitted with sensors for every imaginable component, BMW’s prototypes spew out as many as 15,000 data points from the engine and transmission down to the suspension and brakes. The data reveals errors and error patterns that occur only in certain driving conditions.
“Even if the test driver observes an anomaly like throttle lag or unexpected cornering or shifting characteristics, they can’t tell you why it’s happening,” said Erick Brethenoux, IBM’s director of business analytics strategy, in an interview with InformationWeek. “There are thousands of components in a car that may be contributing to what the driver experiences, and that’s why data analysis is so important.”
BMW has been using IBM’s SPSS Modeler software for more than five years in uses as diverse as manufacturing, warranty, and marketing applications. But until recently, the analysis was typically trained on historical maintenance and repair data collected by dealers, according to Brethenoux. BMW is now using SPSS to analyze all available data sources, including preproduction sensor data.