Advanced Analytics for the Process Manufacturing Industry

Empower process and asset experts with advanced analytics to Analyze, Monitor, and Predict the operational performance of batch, grade, and continuous manufacturing processes.

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Our Software

TrendMiner is an intuitive web-based self-service analytics platform for rapid-fire visualization of time series-based process and asset data.

Available as SaaS, On-premises, or Private cloud solution, the TrendMiner plug and play software adds value immediately after deployment. It enables cross-site teams to collaborate, learn and improve the overall performance of all production facilities.

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LEARN MORE ABOUT THE KEY CAPABILITIES OF TRENDMINER

Industry Leader

We’re excited to announce that we’ve been named an Industry Leader, High Performer, and High performer – Enterprise.

Thank you to all our users for sharing their experiences with TrendMiner.

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Process Manufacturing Challenges

Digitalization

More and more data is being gathered daily from instruments, sensors, and devices.

How can you turn real-time data into real-time performance optimization?

Analytics

Advanced analytics requires expert knowledge of the asset and process behavior.

Is it really necessary to build complex data models for every case?

Transformation

Your company’s process engineers are not data scientists and vice versa.

Can you empower process and asset experts with analytics to let them help transform your business?

Acceleration

Improving the profitability of your company requires acceleration of change.

How can you quickly embed an advanced analytics solution in your organization and successfully manage the change?

LEARN HOW TRENDMINER WORKS

Interested to see what Trendminer can do for your company?

Join the webinar to enrol in the $15K free POC Award

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What if you could…?

Predict maintenance based on process data
See if previous behaviour happened before
Monitor process behaviour real time
Solve 80% of your day-to-day production questions
Optimize energy efficiency

Reduce costs, while improving product quality
Predict heat exchanger fouling
Find root cause through pattern recognition
Send early warnings to the control room
Determine best operating zones based on process data

Process Engineer 4.0

To benefit from the full potential of industry 4.0, process and asset experts must be empowered with analytics to answer their own day-to-day questions. With use of our self-service advanced analytics solution, process engineers will move from analytics aware to analytics enabled up to analytics expert. The new Process Analytics Engineer will be better equipped to improve overall equipment effectiveness, improve product quality and reduce costs.

Self-service Analytics

Classical model-based predictive analytics typically require expensive projects and data science expertise. For many analytics questions it is faster and more efficient to use a self-service analytics tool, designed with operational end-users in mind. Robust algorithms and familiar interfaces maximize ease of use for non-data scientist users. As a result, many cases to optimize the operational performance of the plant can be handled by the people who can really interpret the data.

Actionable Intelligence

What Can You do With TrendMiner?

Analyze

Search, as easy as using Google for process behavior in the past. Diagnose by instantly finding similar behavior with use of our patent pending pattern recognition technology and find root causes to improve your processes.

Monitor

Define optimal processes and set fingerprints to monitor production. These can be used to send out automated early warnings to control room staff in case of deviation, or to capture feedback and leverage knowledge across sites.

Predict

Why react when you can predict the future instead? Use our soft sensor builder, early warning discovery or a unique model-free predictive mode to predict quality, maintenance or future evolutions of batch runs and transitions.

Contextualize

Context can be captured via monitors, manually added, or via business applications. Now you can illuminate your time-series data with context, to get a clear view of operational behavior and improve Operational Excellence faster.