The Power of Machine Learning in the Hands of Operational Experts with Software AG’s TrendMiner MLHub in the New 2022.R2 Release
- TrendMiner’s machine learning hub (MLHub) helps bridge the gap between operations and central analytics teams to bring an even richer overview of process behavior
- Multi-variate scatter plots now can be used for context analytics to get deeper operational insights from process events and third-party information
- Operational story telling improves through new dashboarding options
HOUSTON, TX and HASSELT, BELGIUM and DARMSTADT, GERMANY / ACCESSWIRE / December 15, 2022 / TrendMiner, a Software AG company, introduces MLHub as part of its 2022.R2 release. The new module democratizes machine learning by fostering the creation, training, and deployment of ML models while bridging the gap between operations and analytics teams. The release also includes new context analytics and additional dashboarding features that provide a better view of operational performance.
TrendMiner’s vision to democratize analytics goes beyond its self-service tools. The software provides closer collaboration among a variety of experts to solve operational performance issues. Some require the introduction of (citizen) data scientists who bring specialized techniques and expertise to the table. Keeping data science in the loop allows companies to squeeze the deepest insights out of available data by using advanced statistics and machine learning models.
“After a very successful trial program with notebooks, we are introducing a new industrial MLHub for time-series data,” said Kim Rutten, Machine Learning Product Manager at TrendMiner. “MLHub extends the analytic and machine learning capabilities of TrendMiner. With MLHub, (citizen) data scientists can access unprocessed, processed, and contextualized data in TrendMiner views and validate hypotheses. They also can create, train, and easily deploy machine learning models using the new notebook environment. Such analysis and its results then can be leveraged by other TrendMiner users through machine learning model tags in TrendHub and advanced and interactive visualizations in DashHub. This allows analytics and data science to become a team sport more than ever before!”
Unlike (big) data modelling tools or AI/ML platforms in the context of production process improvements, MLHub makes all pre-processed, time-series, and contextual operational data available for advanced visualizations and machine learning modelling. MLHub supports quick deployment into operations. It bridges the gap between central analytics teams and operations, which allows for fast iterative improvements.
The models developed in MLHub and deployed in DashHub enable operational experts to address and solve even more complex use cases in areas such as safety improvements quality control, sustainability, and overall profitability.
Context Analytics Using Multi-Variate Scatter Plots
Contextualized event data can help identify new areas for performance improvement. TrendMiner provides this from events captured during process monitoring or from data residing in other business applications, such as asset availability data, batch records, lab samples, alerts, and so forth.
The next step in analyzing contextual data is using multi-variate scatter plots. This allows you to plot context events and their attributes on a scatter chart. As an additional benefit, insights through correlations and distributions can be extracted.
Operational Storytelling with New Dashboard Tiles
All the known and new capabilities of TrendMiner 2022.R2 allow for visualization in operational dashboards or production cockpits. Dashboards can be created using trend tiles, context tiles, value tiles, third-party tiles, and the new text tiles and notebook output. This gives a wide variety of data visualization options in dashboards, but also allows for explanations on the dashboards to interpret and understand the information better. With the new text tiles, explanations or instructions can help employees understand the shared reports.
For details about the improvements in the TrendMiner 2022.R2 release, please visit www.trendminer.com. Users of the TrendMiner software will get more information via other communication channels. See it, use it, love it: For an interactive demonstration of TrendMiner’s functionality and to learn how analytics-empowered process and asset experts can help accelerate operational performance, click here.
TrendMiner, of Software AG, delivers advanced analytics software to optimize process performance in chemical, petrochemical, oil & gas, pharmaceutical, food & beverage, metals & mining, water & wastewater, and other process manufacturing industries. TrendMiner unlocks the full potential of IIoT data infrastructure, regardless of vendor, and taps into the available human intelligence for making data-driven decisions. We offer standard integrations with a wide range of data sources, such as OSIsoft PI, Yokogawa Exaquantum, AspenTech IP.21, Honeywell PHD, GE Proficy Historian, Wonderware InSQL, Cumulocity, OSIsoft OCS, AWS S3, SiteWise, Timestream, Microsoft ADL, ADX, TSI, and SAP S/4 HANA DMC.
TrendMiner empowers everyone in manufacturing operations across multiple locations with powerful yet intuitive capabilities to iteratively generate and validate real-time context-aware time-series insights individually and as a team. Search, diagnostic, and predictive capabilities help speed up root cause analysis, define optimal processes, and configure early warnings to monitor production 24/7. TrendMiner helps operators make data-driven decisions to improve production quality, meet business objectives, and increase profitability.
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