IMPROVEMENT OF MULTIVARIATE CALIBRATION THROUGH INSTRUMENT STANDARDIZATION

The successful application of multivariate calibration in solving industrial analytical problems requires a protocol to standardize calibration models between different Instruments, e.g., from a central laboratory instrument to a process instrument. in a previous study, several standardization methods based on the measurement of a small set of standards have been developed and compared to the recalibration on individual instruments. It is shown that comparable standard error for prediction can be obtained standardization, when both instruments involved are of the same quality in terms of prediction performance. Based on the study of a shortwave near-Infrared (SW-NIR) let fuel data set and computer simulation, this paper shows that the standard error for prediction from standardization can be better than that of full set recalibration, when the response on one instrument is standardized into that of a higher quality instrument and the calibration model built on the latter is used for the prediction. This instrument improvement through standardization provides an effective way to avoid on-site recalibration for process analyzers.