This demonstration presentation is part of a series of webinars on Fault Detection and Diagnostic Software tools offered by PG&E. Each session in the series includes a brief overview of the capabilities of the FDD platform before providing a demonstration of the software. This specific session is on ICONICS' Facility AnalytiX.
The ICONICS Suite includes a module for advanced Fault Detection and Diagnostics (FDD). Using FDD, technicians can significantly reduce operational costs, optimize energy consumption, and improve operational efficiency and safety. ICONICS’ FDD module includes both a fault rule engine and a fault rule library, and it supports easy maintenance of fault rules by the facilities operators. The rules engine applies the fault rules against incoming data streams in real-time, and the results are visualized in the ICONICS’ graphics dashboards or exported to 3rd party systems such as Microsoft Dynamics 365 Field Service or other CMMS systems. There is no hard-coded limit to the number of fault rules that can be entered into the fault rule library, or the number of variables/data streams analyzed in a single fault rule. A simple fault rule may compare data from a single sensor (such as the temperature in a room) against a threshold (such as the temperature at which the air conditioning should turn on), whereas a complex fault rule may compare data from five, ten, or even more devices to evaluate whether a system is not configured optimally. It is not uncommon for a company to have hundreds of fault rules for a factory or large campus, and to evaluate them against tens of thousands of data points. ICONICS’ FDD solution is extensible to include IoT, advanced visualization, energy analysis, data historian, distributed alarm management and connected field service worker notification with servers on premises, in the cloud or with hybrid IoT platforms. With the ICONICS’ FDD solution, customers own their own data and have virtually unlimited extensibility options for command and control, analytics, and visualization.