The introduction of process chemometrics into an industrial pilot plant laboratory

Process chemometrics is the application of multivariate statistical methods to industrial process data characterised by a large number of correlated process measurements. In this paper, we aim to show how multivariate techniques have been used in a pilot plant environment with the objective of increasing the general understanding of the process despite having access to limited data. The use of process trajectory plots to follow the operation of the plant are discussed, along with statistical indicators for the detection and diagnosis of process disturbances. The effect of process conditions on product quality is analysed using cross-correlation with latent variables and significant process variables and time delay structures are identified. The experience and process understanding gained by the pilot plant staff has enabled them to propose the installation of new sensors and analysers based upon sound business benefits.