TrendMiner 2019.R3 displays a customized, actionable dashboard with a real-time view of the production process.
TrendMiner, a Software AG company, released TrendMiner 2019.R3, which allows process manufacturing enterprises to build an analytics-driven production cockpit. The software analyzes the live production process, compares its progress to historical production runs, and displays diagnostics, quality status, and predictions to production operators or management through individually designed dashboards. It also streamlines the flow of information between shifts and from shift teams to engineers.
Each stakeholder can have an actionable dashboard, analytics suite, and agile communications facilities with a live overview of the status and performance of the production process. Advanced early warning capabilities give operators the opportunity to act proactively and optimize operational performance before issues arise. Team members can collaborate by sharing items stored in the work organizer.
TrendMiner’s earlier releases allowed process and asset experts to analyze, monitor, and predict operational performance through trend analysis of time-series data. The new release expands on this capability by offering fleet-wide asset performance assessment through cross-asset, value-based search and analytics technology. Engineers can now perform a single value-based search across an entire fleet of associated assets, to compare behavior from different areas of the plant or across multiple plant sites. Through the use of value-based criteria, the behavior of similar assets such as pumps, heat exchangers, and valves can now be directly compared in seconds. The results of such work can be used to create asset-specific production cockpits.
The new software allows integration with business software applications related to production using webhooks. For example, an early warning based on a golden batch fingerprint or best operating zone of an asset can trigger a workflow action in a third-party business application to schedule a maintenance work order.