SAMPLING ERROR IN MEASUREMENT OF DIRT IN PULP AND PAPER

The amount of dirt or impurities in pulp and paper is a critical quali ty characteristic. Manufacturers evaluate dirt content by sampling a s mall potion of their production. In such cases, the estimate of the er ror associated with the measurement is as important as the measurement itself. Whether the analytical procedure is manual or automatic, the randomness inherent in the sampling process is the biggest contributor to variability. This paper presents a theoretical model that explains the observed randomness and provides an equation for estimating the e rror of the measurement. It is proved that if m is the number of impur ities detected in the sample, then l/m(1/2) is a lower bound for the r elative error of the estimate and, in many cases, a good approximation of the expected error.