SMRI leveraged STMicroelectronics ecosystem to develop an Artificial Intelligence based solution to reduce equipment downtime, increase productivity and optimize human intervention by adding predictive maintenance features on industrial equipment.
We needed a predictive maintenance technology that is undeniably proven industrially and whose implementation is agile. After comparing several solutions on the market, we chose NanoEdge AI from STMicroelectronics, the only solution capable of guaranteeing us optimal results, rapid implementation, and the confidentiality of our clients’ industrial data, while providing them with the added value of considerable innovation.
Luc Frison
|
President at SMRI
Approach
Thanks to embedded machine learning, SMRI developed and rapidly implemented predictive maintenance solutions capable of learning, on the field, the different sequences and detect drift in real-time and with a high level of accuracy to plan intervention before major failure.
This solution is running on ultra-low power STM32 microcontrollers.
Sensor
Accelerometer from STMicroelectronics.
