At TrendLab Europe 2024, six of our customers—ICIG, Prax, Synthos, Clariant, CABB, and Sitech—presented their innovative use cases and solutions. If you were there, please pitch in with your learnings and takeaways. Here are mine…
From self-service analytics to large-scale operationalization
A few years ago, the emphasis was primarily on individual root cause analyses and isolated process optimization projects. This year, however, our customers showcased how TrendMiner empowers them to scale their analytics outcomes, supporting large-scale initiatives such as:
- Large-Scale Pump Performance Monitoring: Leveraging TrendMiner to continuously monitor the performance of extensive pump networks, ensuring optimal functionality and timely maintenance.
- Operational Equipment Effectiveness (OEE) Tracking: Utilizing sophisticated analytics to track and enhance the effectiveness of operational equipment across multiple facilities.
- Energy Management: Implementing energy monitoring and optimization strategies at scale, significantly reducing energy consumption and costs.
TrendMiner sits at the core of our customers’ analytics ecosystems, seamlessly unifying data from various sources. This integration enables combined, at-scale analyses and ensures that the actionable insights derived from the data are efficiently communicated to stakeholders across different levels of the organization.
The open architecture of TrendMiner allows it to ingest data from diverse sources and feed the resulting outcomes back into the customers’ ecosystems. This capability remains a key focus for our Product Team, ensuring our solution can adapt and scale to meet the evolving needs of our customers.
Event data and event analytics are key
While time-series analytics remains foundational, many of the showcased solutions also significantly benefit from event data and event analytics. This comes in two flavors:
- Ingesting event data from other sources
For instance, by integrating historic pump downtime data, engineers can analyze pumps’ past behavior to identify periods and causes of decreased performance. This retrospective insight is crucial for predictive maintenance and performance optimization. - Creating and enriching events
Using TrendMiner’s Search and Monitor functionality, periods of decreased production or high energy consumption can easily be detected and annotated, creating meaningful events. These events can be further enriched, either automatically using aggregated time-series data on the annotated time periods or manually based on the operators’ expert knowledge.
The ability to analyze event data, both in TrendHub and ContextHub, has been considerably extended in recent versions of TrendMiner and we’ll continue to build further on this.
Keeping the user experience front and center
Finally, many speakers and attendees highlighted the importance of the user experience and how the user-friendliness of TrendMiner is a key enabler for the adoption of the platform and generating value from advanced industrial analytics. At the event, we launched the Innovator’s Circle and attendees could participate in a prototype test for upcoming event analytics functionality. The opportunity to engage in early testing and provide direct feedback to our Product Team was very much appreciated by the participants and already led to some interesting outcomes that will drive the implementation of this functionality. The user-friendliness of the TrendMiner platform remains a core consideration in our development strategy.
Once again, thank you very much to all speakers and attendees for making this event a success!
Do you agree with the takeaways above? What did you take home from TrendLab Europe 2024? Curious to hear your thoughts...