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Scholars Journal of Physics, Mathematics and Statistics | Volume-5 | Issue-02
Monitoring and Improvement of Water Treatment Process Based On Multivariate Statistical Process Control Techniques
Kalaluka Kalaluka, Romeo Mawonike, Getrude Mambo
Published: March 30, 2018 |
132
61
DOI: 10.21276/sjpms.2018.5.2.3
Pages: 113-123
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Abstract
Water quality monitoring and evaluation provides important information to
estimate water system status. Clean water prolongs someone’s life through equitable
health facility. Residents suffer of unclean water service provided by the utility
Service provider due to lack of sophisticated methods of treatment. This research
seeks to monitor and improve the water treatment process at various stages. In this
regard, multivariate statistical process control (MSPC) techniques specifically, the
multivariate exponentially weighted moving average (MEWMA), the Hotelling’s T2
and the ellipse control charts have been applied to water statistical data. Monitoring
was centred only on two basic water parameters namely; total suspended solids (TSS)
and biochemical oxygen demand (BOD). These two parameters play a pivotal role in
the composition of quality drinking water and they normally exhibit a high
correlation. Results show that the process of treating water for human consumption is
not statistically in control hence requires improvement.