Rank annihilation correction for the amendment of instrumental inconsistencies Original Research Article

The globalisation of the analysis of a series of individual measurements often results in more robust and reliable outcomes. However, instrumental drifts that can occur between individual measurements destroy the ideal data structure and thus the advantages. A method based on rank annihilation factor analysis (RAFA) is introduced for the correction of several types of instrumental inconsistencies. It can be applied to many series of bilinear datasets. Experimental examples discussed in this paper comprise the successful correction of non-uniform retention time drifts in chromatography due to temperature or pressure changes, wavelength shifts in IR spectroscopy in an industrial control situation, and background absorption shifts in UV–VIS spectroscopy applied to equilibrium investigations.