Feb 01, 2021

            Software AG’s TrendMiner 2021.R1 release puts data science in the hands of operational experts
        

  • Embedded notebooks that bridge the knowledge gap between engineers and data scientists
  • Multiple asset framework support that eases enterprise roll outs
     

Houston, Texas, U.S., Hasselt, Belgium and Darmstadt, Germany – Software AG’s TrendMiner has announced the release of TrendMiner 2021.R1. This latest release brings a completely new functionality of notebook integration, which helps users access both data dashboards and code-based data analysis. Also in 2021.R1 are extended capabilities to support multiple asset frameworks and many new user-driven features to help end users improve operational performance and overall profitability.

Bridge the knowledge-gap between engineers and data scientists with embedded notebooks
TrendMiner enables operational experts in process industries to analyze, monitor, and predict operational performance using sensor-generated time-series data. The goal of TrendMiner has always been to empower engineers with analytics for improving operational excellence, without the need to rely on data scientists. In doing so, TrendMiner brought data science to the engineer. In the 2021.R1 release, TrendMiner makes the next step of this journey by integrating notebook functionality into the software so that users can easily jump from looking at data in a TrendMiner view to working with it in a code-based data science environment.

With their data science libraries of choice (e.g. Pandas, NumPy, SciPy, SciKit-Learn), engineers can create and run custom scripts themselves for advanced statistical analyses and use AutoML capabilities to build machine learning models for anomaly detection. On top of that, they can operationalize the resulting notebook visualizations (also created with libraries of their choice such as Matplotlib, Plotly, Seaborn) as dashboard tiles in TrendMiner DashHub.

Thomas Dhollander, CTO at TrendMiner commented, “Classical data science depends on bringing process / asset know-how to the data scientist, while self-service analytics aims at packaging a subset of data science modeling capabilities and bringing these to the subject matter expert as a robust set of features (no technical tuning parameters, no data science training needed). Companies that recognize the potential in interweaving these complementary approaches will be the ones that can accelerate their operational efficiency and competitive advantage.”

Support for multiple asset frameworks for globally operating users
To support enterprise rollouts and the increased complexity of existing IT-landscapes, TrendMiner has extended its capabilities for handling multiple plant breakdown structures also known as asset frameworks. OSIsoft PI users can easily connect multiple OSIsoft PI Asset Framework servers and set access permissions. Besides support for multiple PI AF structures, multiple CSV asset trees can be imported for use as a data source within TrendMiner. As a result, System Administrators can better control accessibility with the ability to publish and unpublish structures, while the users have more flexibility to analyze the operational performance of multiple plants and production lines, each with their separate plant breakdown structures.

Further information
In each release, TrendMiner adds a new range of features and enhancements that are requested by its users. There are many more improvements in the TrendMiner 2021.R1 release, which users can find in the TrendMiner release notes on the website: www.trendminer.com. To see TrendMiner’s functionality in-action and learn how analytics-empowered process and asset experts can help accelerate operational performance and increase profitability, click here to request a demo.

About TrendMiner
TrendMiner, a Software AG company and part of the IoT & Analytics division, delivers self-service data analytics to optimize process performance in industries such as chemical, petrochemical, oil & gas, water & wastewater, pharmaceutical, metals & mining, and other process industries. TrendMiner software is based on a high-performance analytics engine for time-series data that allows users to question data directly, without the support of data scientists. The plug-and-play software adds immediate value upon deployment, eliminating the need for infrastructure investment and long implementation projects. Search, diagnostic, and predictive capabilities enable users to speed up root cause analysis, define optimal processes, and configure early warnings to monitor production. TrendMiner software also helps team members to capture feedback and leverage knowledge across teams and sites. In addition, TrendMiner offers standard integrations with a wide range of historians such as OSIsoft PI, Yokogawa Exaquantum, AspenTech IP.21, Honeywell PHD, GE Proficy Historian, and Wonderware InSQL.

Founded in 2008 and now part of Software AG, TrendMiner’s global headquarters is located in Belgium and has offices in the U.S., Germany, Spain, and the Netherlands.