Machines, devices and industrial equipment generate more and more data that is easier to collect using the IoT. This data is full of hard to extract valuable information.
Yazzoom’s machine data analytics and anomaly detection solution uses artificial intelligence to automatically learn normal machine operations and detect anomalies in sensor data and log files
It is used to (remotely) monitor machines and have an early detection of technical issues, speed up (remote) diagnostics of the root cause of machine failure and reduce the mean time to repair, extract the typical usage patterns of a machine fleet to improve the design and engineering of the next generation and more.
Thanks to its flexible architecture and data agnostic machine learning algorithms, it has a proven track record on a variety of machine and data types: industrial production lines (continuous and batch processes, robot-powered discrete manufacturing), medical imaging equipment, network and telecom infrastructure, IoT-enabled utilities networks, power plant systems, consumer connected devices…