With the advent of the 4th Industrial revolution, referred to as Industry 4.0 or the Internet of Industrial Things (IIoT), machines and systems are becoming more intelligent and better connected at a rapid pace. This connectivity has enabled data from the operational domain - the OT, to reach into the IT domain. The combination of connectivity and the proliferation of sensors generating data has created a tidal wave of information that before was not readily accessible, and yet holds the key to unlocking more efficient and reliable operations of these connected machines and systems. Companies that understand and are aware of the IIoT, recognize that they need to adapt to the challenges of the next phase of Industrial revolution and continue to reduce operating costs.
One particular means to accomplish this reduction is to maximize their assets by minimizing downtime. Using sophisticated data analytics, combining the wealth of sensor data and other asset-related lifecycle parameters, companies are starting to move away from “Preventative” maintenance and focus more on “Predictive” maintenance. Using this approach, companies can begin to keep their assets operating more efficiently, more reliably with longer periods of up- time, without taking their assets offline, avoiding costly downtime for regularly “scheduled” maintenance. By increasing uptime, companies can keep their assets operational until the data analytics indicate a specific asset or part of an asset that is approaching the need for maintenance and thereby avoiding potential costly system failure.
Xilinx technologies facilitate the move to predictive maintenance by providing the link between the sensors generating the data and the processing of the data. Through highly configurable I/O, HW and SW processing, filtering, pattern detection and analysis, in many cases in real-time, Xilinx technology is used to ensure that the essential sensor data required for an accurate predictive maintenance determination is communicated and provided in advance of asset or system failure.