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Wastewater plant data, especially suspended solids and BOD data have an inherent variability of 10–30%. Use of this data to calculate MCRT, F/M loadings, sludge wasting targets, etc without accounting for the variability can lead to inaccurate calculations, constant overcorrection and excessive variability. In some ways the data are like quantum mechanics: the value of an analyzed sample is not a precise point, but rather a point in a data cloud of probable values (it's in here somewhere). Attempts to control the process based on data values that are actually not deviations from a set point, but are in fact just random “noise” will produce overcorrection and an increase in the standard deviation of a controlled value. The doughty operator need not despair: there are several easy techniques to reduce the data variability that do now require new equipment or a PhD in statistics. These techniques include:

Use of composite samples to reduce variation

Increased sampling to acquire more data

Use of moving averages and easy data smoothing

Use of control limits to determine when to change wasting

This paper will show how to reduce variation in data and how to reduce variation in the operator's daily life.

Document Type: Research Article


Publication date: 2005-01-01

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