In today’s automotive industry, it is more important than ever to efficiently assess the unit under test and create valid result data. This fact applies to everything, from R&D testing to production testing. Early detection of problems is crucial to prevent costly damage to the unit under test and delays in the project schedule. Since tests are usually executed over several days and weeks, an intelligent mechanism is needed to detect errors and anomalies at an early stage.
In this free, 60-minute webinar, experts from AVL will explain how Machine Learning can be used to intelligently monitor the health of the unit under test and the overall system. The experts will also demonstrate a solution using a real-world use case.
Key takeaways:
• Applied Machine Learning in test bed automation
• Increased test efficiency due to early anomaly detection
• Use cases for various application areas, like Fuel Cell, Battery, E-Motor