Multivariate quality control of lubricating oils using fourier transform infrared spectroscopy

Abstract

Multivariate quality control in conjunction with Fourier transform infrared Spectroscopy (FTIR) were used to qualitatively detect the class and the condition of lubricating oils. The multivariate approach was based on principal component analysis (PCA), first to classify the lubricating oil type (mineral, synthetic and semi-synthetic) and then to develop two control charts: a T 2 chart using the most significant principal components and a Q chart with the PC not used in the first chart. From these two charts it was possible to identify oil samples, based on a viscosity parameter, which were out of the pattern normally present in utilizable lubricating oils.