With 50 to 5000 channels, engineers can quickly spend millions and months or longer on physical testing. A more efficient test plan without under-testing is critical.
Test plans are inefficient
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You need to speed up time-to-market without risking product safety or brand reputation. Yet, you face three underlying challenges:
Test data has undetected errors
Test systems generate terabytes of sensor data weekly. Unfortunately, measurement errors from sensor failures or configuration mistakes result in costly retesting and schedule delays.
Failures are costly
Late-stage product validation failures put brand reputation and budgets at risk. Detecting and understanding the root cause of failures is critical for fast reaction time and quick fixes.
There are many potential use cases for AI to speed up the battery test and validation process. After an extensive evaluation, we found Monolith to be an excellent option for scaling AI across our R&D.
-Markus Meiler, VP Research & Development, Webasto
