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Process Optimization Software | Process Analytics

Optimize assets and processes – from plant-level operations to the enterprise – with self-service process analytics software.

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Software for industrial networks | GE Digital

What is TrendMiner Process Analytics?

TrendMiner is an intuitive web-based industrial process analytics application to perform visualization of large amounts of sensor-generated time-series and contextualized data. The solution enables process optimization through its enhanced functionality for process monitoring, troubleshooting, and embedded problem-solving capabilities.  


GE Digital has partnered with TrendMiner, a Software AG Company, incorporating process analytics with its Asset Performance Management (APM) portfolio. This strategic partnership provides customers in industries like oil and gas, metals, mining, and petrochemicals the ability to optimize assets and processes from plant-level operations through to the enterprise.


Get the right insights, right on time

Identify & use trends without needing a data scientist

This self-service model automatically meets the high demands of time-series industrial process analytics. Process engineers receive highly visualized data in trend views, root causes, and performance monitoring in real-time.

Make data-driven decisions and continuous improvements

Break down contextualized data silos residing in various business applications to shed new light on your production’s processes and enable a proactive approach to process improvements.

Achieve sustainable value for your production processes

Empower subject matter experts to make impactful production decisions and contribute to overall enterprise performance objectives. Self-service analytics allow engineers and operators to dive into improvements on overall equipment effectiveness, waste reduction, consistent production quality, carbon reduction, and the operational safety of your team.

Key Capabilities

TrendMinder TrendHub


Analyze, monitor, predict using time-series analysis  

  • Google-like search for Root Cause Analysis 
  • Pattern recognition, filtering, and layer comparison 
  • Monitor by operating zones, receive early warning and notifications 
  • Model-free performance predictions and predictive maintenance  
TrendMinder ContextHub


Contextualized Data 

  • Receive analytics for all contextualized data including other business applications (ERP, Batch, CMMS, LIMS etc.) 
  • Quickly drill down from process events to underlying time series 
  • Streamline team communications, collaboration, and approval flows 
  • Capture knowledge and trends 
TrendMinder DashHub


Visualization using Dashboards 

  • Summarize trends, context, alarms, and value indicators 
  • Multiple dashboards and prioritized areas of interest 
  • Facilitate shift handovers, production meetings and other team activities 
  • Reporting  
TrendMiner MLHub


Machine Learning (ML) 

  • Flexible ML model creation using built-in toolkits or use third-party modeling 
  • Clean data collection to create finite data frames for deeper analysis 
  • Preloaded open-source algorithms or import from other tools 
  • No-code interface leveraging machine learning results designed for any operations user to gain deeper insights on process behavior 
  • Cross-platform interoperability with TrendHub, ContextHub, and DashHub 

Ready to get started?

Contact us to learn more about how process analytics can help you search for trends with ease and analyze process data directly to avoid production loss and boost overall production performance.  

Complimentary Software

APM Health software from GE Digital helps petrochemical plants reduce asset performance risk
Industrial Apps

Asset Health & Condition Monitoring

Standardize the collection, integration, modeling, and analysis of disparate data into a single, unified view.

APM Reliability software helps the bottling industry improve operations performance
Industrial Apps

Reliability Analysis Software

Achieve less unplanned downtime by predicting equipment issues before they occur.