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Dynamic mass balancing for wastewater treatment data quality control using CUSUM charts
1Institute of Water Quality and Resource Management, Vienna University of Technology, Wien, Austria. a.spi@iwag.tuwien.ac.at
Summary
Mass balancing is key for wastewater data quality control. Statistical process control using CUSUM charts effectively identifies periods of stable, low mass balancing errors, improving data precision assessment.
Area of Science:
- Environmental Engineering
- Water Treatment Technologies
- Data Quality Management
Background:
- Mass balancing is a standard method for data quality control in wastewater treatment.
- Existing methods like mean balancing error have limitations in detecting systematic data errors.
- Statistical process control offers robust tools for analyzing data variability and error patterns.
Purpose of the Study:
- To introduce the CUSUM chart method for analyzing mass balancing errors in wastewater data.
- To demonstrate the effectiveness of CUSUM charts in identifying periods of stable, low mass balancing errors.
- To highlight the importance of balancing error variability as a measure of data precision.
Main Methods:
- Application of the CUSUM (Cumulative Sum) chart, a statistical process control technique.
- Analysis of the error vector derived from mass balancing data in wastewater treatment.
- Evaluation of two case examples to illustrate the method's performance.
Main Results:
- The CUSUM chart method successfully detected time periods with consistently low mass balancing errors.
- The detectability of these stable periods is directly influenced by the variability of the mass balancing error.
- The study confirms the CUSUM chart's utility in identifying precise data periods.
Conclusions:
- CUSUM charts provide an effective enhancement over traditional mean balancing error for wastewater data quality control.
- The variability of mass balancing errors is a critical indicator of data precision, reliably assessed by CUSUM charts.
- This statistical approach improves the identification of reliable data segments in wastewater treatment processes.
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