We have strategically decided for edge computing as an essential feature of our solution. The capability of processing large amounts of data without cloud infrastructure has many benefits. Firstly, the cost of cloud computing is quite high. Secondly, the local process allows immediate reaction and machine-to-machine integration. The data also stays within the factory network perimeter. We can also analyze every second of every minute all year around. That is TB of data every month from a single machine. In addition, there is now issue with the communication bandwidth.
We have proven that neural networks are very effective in anomaly detection. We have hundreds of hours of broken machines of all types in our database. As we have also implemented the traditional vibro diagnostic heuristics like signal envelope methods based on the RPM, we can compare the new approach and traditional techniques. The neural networks can detect coming issues more than 4x likely and sooner than the current methods (89% compared to 19%). Our goal is now to work with Large Enterprises and OEMs, who want to innovate their machines monitoring system. We also started working on building the distribution network of value added resellers, so we can roll-out our solution at the global scale.
September 2023 | Pavel Konečný for TechFounders