LinePulse can be used to automate root cause analysis in the manufacturing of complex automotive assemblies, like electric motors. Here is an example.
Manufacturing analytics use cases
Predictive quality and advanced analytics projects that help manufacturers solve production problems
Nissan collaborated with Acerta to develop a failure prediction system for vehicle components. Through a combination of data sets and machine learning algorithms, a prototype was created that accurately estimates engine health and predicts the remaining driving distance until failure.
Leak testing can be a time-consuming and delicate process but it’s critical that manufacturers get it right. This use case describes how EV battery manufacturers can ensure quality with advanced analytics from their manufacturing data using LinePulse.
Injection molding requires a high degree of technical expertise to execute successfully. This manufacturing analytics use case describes how LinePulse provides advanced warning of potential defects, so operators and engineers can intervene proactively and prevent scrap.
A major European OEM enlisted Acerta to develop a machine learning model that would identify a failure in components of vehicle suspension sub-assemblies.