Yukio Hiraoka

A Monitoring Technique Using Multivariate Statistical Process Control Method for Performance Improvement with Application to Wastewater Treatment Plant Operation

Abstract This paper presents a new monitoring technique to improve the performance of plant operation based on multivariate statistical process control (MSPC). The proposed method combines with MSPC by principal component analysis (PCA-MSPC) and monitoring of a predefined performance index for efficient and stable plant operation. Fault detection and isolation (FDI) related to the performance index is selectively performed by monitoring the time series data of the index wherein the sample points violating the control limit of the Q statistic or that of the T 2 statistic in PCA-MSPC are indicated. Hidden patterns of probable cause to deteriorate the performance index are discovered from the FDI by observing the time series data of the isolated variables. Applications of the proposed method to real wastewater treatment process illustrate the effectiveness of the proposed method by showing possible improvement for energy-saving operation and stable plant operation.