Analysis of Residual Chlorine in Water Production using MEC Control Charts with Fast Initial Response Features
DOI:
https://doi.org/10.30656/jika.v6i1.11687Keywords:
Quality Control, Residual Chlorine, MEC Control Chart, Fast Initial Response (FIR), Water ProductionAbstract
Problems: Residual chlorine is a crucial parameter in water production processes to ensure microbiological safety. However, conventional statistical process control charts often exhibit limited sensitivity to detecting small, early shifts, particularly during the initial monitoring (startup) phase. Excessive or insufficient residual chlorine levels may pose health risks and indicate instability in the production process, highlighting the need for more responsive monitoring tools.
Purpose: This study aims to evaluate the performance of the Mixed EWMA–CUSUM (MEC) control chart integrated with Fast Initial Response (FIR) and Modified Fast Initial Response (MFIR) features in monitoring free residual chlorine levels in water production systems.
Methodology: This study employs a quantitative analytical approach using secondary data obtained from a real water production process. The MEC control chart combines the strengths of EWMA and CUSUM to improve sensitivity to small shifts, while incorporating FIR and MFIR features to enhance early detection during the startup phase. Various parameter combinations are examined to assess detection behavior and control limit characteristics.
Results/Findings: The results indicate that the MEC control chart with MFIR features provides earlier and more sensitive detection of potential process deviations compared to conventional approaches. In particular, the MFIR chart with parameters and produces narrower control limits during the initial phase and identifies three out-of-control observations. These findings demonstrate that integrating MFIR into the MEC framework enhances early-stage monitoring performance and offers practical benefits for residual chlorine surveillance in water production systems.
Paper Type: quantitative analytical research
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