Ponente
Descripción
Sometimes analytical laboratories receive requests with a small number of determinations and/or a small number of samples, or outside the typical scope of analytical services. As a result, they may not have historical data on the performance of analytical processes and/or appropriate reference materials. Under these conditions it is difficult or uneconomical to use traditional quality control charts. This is the so-called start-up problem of these charts. The Quesenberry’s Q charts for the process mean and variance seem the most appropriate charts under these conditions because they do not need any prior training phase. This experimental study of Q charts for individual measurements was done with data from quality control for the evaluation of mass fraction of Ni, Al2O3, Co, SiO2, Cr2O3 and Fe in a laterite and a serpentinite CRMs by ICP-OES. The performance of these Q charts is discussed when the analytical process is in the state of statistical control, in the presence of outliers at the start-up, a persistent systematic error, simultaneous small drifts of mean and variance, a gradual increase of the mean and a small autocorrelation of the raw data. The performance of Q charts was in agreement with the numerical simulation studies discussed in the seminal reports by Quesenberry. This study is the first systematic experimental confirmation of the benefits of Q charts for ad hoc tasks.
