SINTEF, DENO, NXTECH, ILABS

The predictive maintenance demonstrator offers a solution to implement an intelligent monitoring system that separates the equipment's normal condition from abnormal conditions. IIoT-based sensors are installed to measure different parameters such as vibration, current, sound, temperature, etc. The maintenance is today preventive in the soybeans production facility. Advanced predictive maintenance solutions reduce downtime and potential breakdowns. Today there is equipment that has no or little communication back to the control system, and it is challenging to determine the actual fault that causes a stop on the equipment. The measurements depend on the type of equipment, and the chosen equipment in predictive maintenance demonstrator is based on historical faults in the production line. Data from the IIoT devices are sent to AI-based models that correlate with normal and abnormal conditions.


Beyond state-of-the-art developments and impacts


The maintenance concept is based on the combination of technical, supervisory, and managerial actions performed during the life cycle of the equipment/motors to maintain the soybean production and provide an enhancement through the introduction of AI-based, real-time sensor monitoring.