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Monitoring chemical processes for early fault detection using multivariate data analysis methods

FREE WHITEPAPER: Monitoring chemical processes
Multivariate statistical methods can be used to monitor process variables and predict final product quality at an early stage, while also providing deeper understanding of the process compared to traditional statistical methods.

This allows engineers and production managers to:
  • Optimize their processes
  • Reduce failures
  • Realize significant cost and time savings

This whitepaper includes:

  • A real-world example from a manufacturing company that was able to improve product quality by better understanding key process variables
  • A background and explanation of some of the key multivariate methods
  • Examples of how to interpret typical multivariate plots

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About CAMO Software

Founded in 1984, we are a leader in Multivariate Data Analysis and Design of Experiments software. More than 25,000 data analysts, engineers, researchers and scientists use The Unscrambler® X suite to explore and analyze large data sets, improve product development, manufacturing processes, quality control and market segmentation.

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