December 7, 2018 –TrendMiner NV, a Software AG company, has announced their latest software update: TrendMiner 2018.R2. The release includes a set of capabilities, collectively called ContextHub. Other additions include: OSIsoft PI Event Frames integration, a related context item search for filtering of time-series data, and further extensions to the recommendation engine that helps operators and engineers to speed up root cause analysis of process anomalies.
TrendMiner enables process and asset experts to analyze, monitor and predict operational performance through trend analysis of time-series data. The introduction of ContextHub works to increase the flexibility of annotation, providing process and asset experts brand-new insights into their data. ContextHub is a repository, search engine, and collaboration platform for context items that can be neatly aligned to assets, processes and events. The platform can be configured for context itself to become a powerful new dataset that can be both visualized and analyzed. It also serves as a starting point for time-series analytics.
Context items can be automatically captured, manually entered, or easily imported from other manufacturing solutions, such as Batch systems (i.e.OSIsoft PI Batch), Laboratory Information Management Systems, Computerized Maintenance Management Systems and Overall Equipment Effectiveness (OEE) systems, thus maximizing the flexibility of contextual information.
TrendMiner, already deeply integrated with OSIsoft Asset Framework, now provides out-of-the box access to both historical and new Event Frames for OSIsoft PI System users and others. These ecosystem synergies give OSIsoft customers a way to gain access to Event Frames information, click through the related information, and kick-start their discovery and diagnostic analysis.
The ability to search for context items gives users the power to actively employ gathered context as part of the TrendHub analysis itself. It enables users to select saved ContextHub views from which they can visualize, filter or overlay time periods in TrendHub. Context items can now become a rapid starting point for trend analysis and facilitate filter requirements through all time series data. This capability also effectively speeds up root cause analysis or can even create fingerprints and monitors that can be used to send notifications to the control room and adjust process parameters when necessary.
TrendMiner is designed by engineers for engineers and highly values user feedback. Each release includes improvements based on user ideas and suggestions. The most important enhancements in the TrendMiner 2018.R2 release include:
Hierarchical organization of saved fingerprints, which help monitor process performance.
Fingerprints used to monitor process performance can now be used for early warnings. This will help avoid the trigger of hard alarms and support control room personnel to take appropriate action.
For diagnostic analysis, TrendMiner provides a compare table showing the statistical difference between a range of tags of interest that can be exported as xls-file to be used in other systems.
Further extension of the powerful Recommendation Engine capabilities. This machine learning tool now uses the matching patterns found in the historical data to recommend potential root causes for process anomalies, which increases the likelihood of recommendations.
The full range of capabilities plus the new ContextHub and the several usability enhancements will serve to further reduce the time and effort it takes to solve equipment and process performance related issues. It is TrendMiner’s goal to help customers make better, faster decisions by giving the power of analytics to the people who can interpret the data.