Case Studies

Identifying gear tooth fractures that were missed in end of line testing.

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.

AI recommendations for axle assemblies reduce rework rate by 65%.

Identifying the earliest indicators of engine misfires in real time.

Reducing signals that required manual investigation for root cause analysis by 99.75%.

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.

How can we Help?