Monitoring Chemical Processes For Early Fault Detection Using Multivariate Data Analysis Methods

By Dr Frank Westad, Chief Scientific Officer, CAMO Software

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. This allows engineers and production managers to optimize their processes, thereby realizing significant cost and time savings.

This white paper includes a background and explanation of some of the key multivariate methods, as well as examples of how to interpret typical mulitvariate plots. It uses a real-world example from a paper manufacturing company that was able to improve a key quality parameter, Print Through, by better understanding the variables impacting it.