We developed our platform to allow our clients to access the full potential of their collected data.
Each one of our solutions was designed to extract the maximum value for the client based on the data they collect. They all provide actionable insight to support analysis and decision-making, thus saving millions of dollars in warranty claims, repair and maintenance costs, manufacturing downtime, and legal expenses.
During pre-production road testing, Acerta’s platform analyzes the data coming from the hundreds of sensors mounted on the vehicle, and provides actionable insight in real-time. Designed to work with dynamic and highly contextual data, it identifies anomalies in the data and assists engineers with root-cause analysis by pointing to the handful of signals that are most indicative of the anomaly. By leveraging the power of machine learning, our platform helps detect elusive issues that would otherwise be discovered in the later, more costly phase of serial production.
Acerta’s analysis of End-of-Line Testing data augments existing test processes by looking deeper into the data than any current mathod. It goes beyond statistical process controls and uses deep artificial nural networks to map and understand the complex correlations between the data coming from the vehicle's various subsystems, and to automatically detect hidden anomalies. This assists engineers in identifying faulty systems that would otherwise be sent to a client and fail during the warranty period.
Acerta’s In-Field Monitoring & Prognostics provides automatic health monitoring for mechanical systems. Our neural net platform learns the behavior of the various data streams from these systems in real-time, and evaluates their remaining useful life based on the subtle fluctuations and variations in the different signals over time. Our In-Field Monitoring & Prognostics solution enables our clients to shift from preventive to predictive maintenance and significantly reduce expenses on maintenance, warranty and repairs. The dynamic nature of our algorithms is key to their effectiveness and makes them ideal for analyzing automotive data