Identifying the earliest indicators of engine misfires in real time.
Reducing signals that required manual investigation for root cause analysis by 99.75%.
Identifying gear tooth fractures that were missed in end of line testing.
AI recommendations for axle assemblies reduce rework rate by 65%.
Identifying faulty EPS systems with 0% false negatives and <1% false positives.
Predicting engine failures with 93.3% accuracy, accelerating diagnosis and root cause analysis.
Learn more about Implementing Machine Learning with LinePulse
Using vehicle data to detect changes in road surface in <1 second.
Predicting engine failures 400km in advance using ECU data.
Detecting steering misalignments and loose suspensions with 100% and 95.8% accuracy, respectively.
Reducing time for root cause analysis from 2 weeks to 60 minutes.
Upgrading from electrochemical models to machine learning for more dynamic analysis.
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