Root-Cause Analysis

Your team needs to find root causes of process anomalies, explain quality defects, or assess the effect of equipment upgrades?

Visplore offers process engineers a  unique workflow for understanding process changes in no time – even without initial hypothesis.

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See 2 Minutes Of Root-Cause Analysis In Action

Empowering Process Experts With Advanced Analytics
Identify & Compare changes in process parameters – as easily as never before

Let Visplore identify suspicious process parameters and generate expressive visualizations. So that your process experts can focus on interpreting the patterns with their knowledge. And make informed decisions about actions.

  • Connect to files, data bases, or the PI system
  • Select and compare time ranges in three clicks
  • Identify changed parameters automatically
  • Find also unexpected co-occurrences at a glance
  • Apply to continuous & discrete process data
  • Adopt a standardized and robust workflow
  • Understand thanks to expressive visualizations
  • Get started even without initial hypothesis

Learn about use case examples and best-practices in our blog post.

The five top-ranked process parameters that show significant changes of their levels some time before the anomaly started.
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Finding changed process parameters causing increased scrap production.
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Scaling Root-cause Analysis for the big data era

A key driver in today’s industry is the need to decrease the consumption of energy and natural resources while ensuring the stability of the production process. To this end, companies are investing heavily in sensors along the process chain and enhanced data management. Due to the sharply increasing number of sensors, experience alone is often no longer sufficient to identify process parameters which indicate root causes of process anomalies. Hundreds or even thousands of process parameters may need to be considered. This is very tedious and time-consuming with standard monitoring tools.

At Visplore, we believe that data-based process optimization is most successful when process experts are empowered to answer complex questions themselves while being supported by advanced analytics and expressive visualization.

Why our customers
prefer Visplore

Perfect for dirty sensor data. With Visplore, we give customers more insights for the same money.

When we need it fast, we use Visplore.

Visplore enabled us to gain significant new insights from massive data about the impact of production process parameters on product quality.

Thanks to its ease of use and high performance even with millions of measurements, Visplore has established itself as our standard tool for quality management in plants from China to South America.

Checking and cleaning data from energy systems used to be very time-consuming and kept us from our core tasks. With Visplore, data preparation has become much faster, and the quality of the resulting data has improved.

The good usability and the comprehensive visualizations enabled us to gain a deeper understanding of routinely collected data and their relationships. For example, this increased the quality of forecast models.

Visplore is recognised and in use as a central strategic software for data analytics throughout the company.

By analyzing process data from a large foundry with Visplore, complex dependencies were detected that we didn’t find with other software. As a result, our customer’s heat energy was reduced by around 5% and mold wear by around 4%.

For our thermodynamical simulations, Visplore helps us to identify suitable data, eliminate outliers, and analyze physical processes very effectively.

The visualization is fast and simple enough for live collaboration with the customers, on site. By this, Visplore supports a thorough understanding of correlations, outliers, and anomalies.

Visplore makes our analysis of sustainable energy systems much more efficient.
In addition to the performance for large data, its integration with scripting environments is a big plus.

Visplore allows for a much easier investigation of relevant patterns and structures. Our downstream analysis becomes more efficient and we gain more confidence in the results.

 
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GF
Verbund
APG
AIT - Austrian Institute of Technology
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Find root-causes like never before.