Automates real-time issue detection for SMEs, enabling quick responses and faster troubleshooting with custom annotations and metadata.
An issue that stems from enhanced monitoring and data analytics is the ability for SMEs to pick-up and react to real-time issues with access to an entire human’s memory of previous and potential issues.
However, the fault annotation library brings anomaly detection and profile recognition to a new front, allowing SMEs to be proactive and ahead of schedule. The interface withholds a simple user experience that gives SMEs the ability to quickly and effectively respond to annotations made previous by users, or by ML, and automatically allocate these anomalies alongside their metadata based off real-time data
The fault annotation library brings value in the following points:
1- A database of custom annotations and data profiles made unique to an organization.
2- To automate the effective response if annotations align with process data.
3- Troubleshooting can begin a step ahead, reducing the time allocating and analyzing the data, by allowing SMEs to jump directly to the period of interest with the relevant KPI’s.
