A new approach to multivariate statistical process control and its application to wastewater treatment process monitoring

Osamu Yamanaka; Ryo Namba; Takumi Obara; Yukio Hiraoka

doi:10.36001/ijphm.2024.v15i3.3854

A new approach to multivariate statistical process control and its application to wastewater treatment process monitoring

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Published Oct 8, 2024

DOI https://doi.org/10.36001/ijphm.2024.v15i3.3854

Osamu Yamanaka

a:1:{s:5:"en_US";s:56:"Toshiba Infrastructure Systems and Solutions Corporation";}

Ryo Namba Takumi Obara Yukio Hiraoka

Abstract

This paper presents a new process monitoring and fault diagnosis approach based on a modified Multivariate Statistical
Process Control (MSPC) and evaluates its applicability to municipal wastewater treatment process monitoring. Firstly,
a conventional MSPC, based on Principal Component Analysis (PCA), is adjusted to provide an easy-to-understand user
interface and then a new yet simplified reconfigurable diagnostic model is introduced. The user interface that has been
developed is designed to integrate MSPC seamlessly with existing process monitoring systems that use the so-called trend
graphs. The proposed diagnostic model is constructed by aggregating small models with either one or two inputs, which
enhances the tractability of the diagnostic model. The effectiveness of the modified MSPC is demonstrated through a series of offline and online experiments, using a set of real multivariate process data from a municipal wastewater treatment.
plant.

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References

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