A variety of quality control (QC) analyses are performed with regular
frequency in environmental chemical measurements. Typically, an accept
able result must be obtained for each QC check before measurement of e
nvironmental samples may begin, and each check is periodically repeate
d to validate the analyses of intervening samples. Corrective actions
are performed if the check is failed, and the intervening batch of sam
ples are remeasured. Under such a scheme, excessive costs will occur i
f the quality control checks are too frequent (i.e., batch size is too
small) or infrequent (i.e., batch size is too large). This paper desc
ribes an approach for investigating the frequency of QC checks for min
imizing the expected cost of measuring a set of samples. Two specific
expected cost models are discussed. It is shown that the empirical est
imate of measurement drift can be used along with computer simulation
to estimate the batch size that will minimize the expected cost of sam
ple analyses. Measurement drift of inductively coupled plasma mass spe
ctrometry for Sb-121 is demonstrated with data from standard reference
materials repeatedly analyzed between QC solutions. Examples are pres
ented using computer simulation and empirical estimates of linear drif
t functions for analytical measurements.