Today's leading manufacturing companies need to make better, faster business decisions using data-driven insights. The key is to unlock the hidden value of all factory data worldwide. This is achieved first by aggregating global operational data in real-time into a centralized data management platform that has unlimited scalability, thereby unlocking and reconciling information stranded in legacy & silo systems. Next is the ability to sanitize and contextualize large amount of data ingested while securely transmit sensitive manufacturing data from production shopfloor to enterprise cloud. Such unified view of all operational data provides the foundation upon which industry-proven analytical/AI software can derive models that self-optimize productions, predict failures, and minimize consumptions.

In manufacturing, one breakthrough application of such AI software is in Prescriptive Maintenance. With advancement of AI, autonomous AI agents can be deployed online to recognize minuscule pattern changes across numerous real-time sensor data of an equipment to detect early symptoms of equipment degradation that neither humans nor sensors alone are capable of detecting. These AI agents can predict when and how equipment will fail, provide complete FMEA (Failure Mode & Effect Analysis) and prescribe early corrective actions to avoid damage that leads to shutdown. Early detection may only require simple maintenance, and in most cases, notification will occur weeks in advance, allowing equipment to be taken offline at a convenient time when production demands are lower. This result in significantly lower repair costs and increased production.