AI solution for industrial predictive maintenance with Oxytronic
Predictive maintenance solution for industrial equipment.
Oxytronic leveraged STMicroelectronics ecosystem to develop an AI-based solution to add predictive maintenance features to any industrial equipment. Predictive maintenance solutions enable to reduce equipment downtime, increase productivity, and optimize human intervention.
The NanoEdge AI studio solution has enabled us to launch the realization of the IRMA predictive maintenance sensor, with our own teams, without having to recruit machine learning experts.
Serge De Senti
President at Oxytronic
Approach
This solution can be adapted to any industrial equipment. The on-device learning capability of NanoEdge AI Libraries enable to perform incremental learning to tailor the model to a specific piece of equipment in every environment. The solution can then detect any drift in real time and with a high level of accuracy. Alerts are sent through various communication protocols to inform the maintenance teams, so they can carry out physical adjustments before major failures occur. This is achieved thanks to the Machine Learning algorithm running on an ultra-low power STM32 microcontroller.
Sensor
Accelerator, environmental sensor and microphone from STMicroelectronics.
Resources
Code optimized with NanoEdge AI Studio
A free AutoML software for adding AI to embedded projects, guiding users step by step to easily find the optimal AI model for their requirements.
Running on STM32WB series
The STM32 family of 32-bit microcontrollers based on the Arm Cortex®-M processor is designed to offer new degrees of freedom to MCU users. It offers products combining very high performance, real-time capabilities, digital signal processing, low-power / low-voltage operation, and connectivity, while maintaining full integration and ease of development.
