Acid number, viscosity and end-point detection in a multiphase high temperature polymerisation process using an online miniaturised MEMS Fabry-Pérot Interferometer

Abstract Recent advances in the latest generation of MEMS (micro-electro-mechanical system) Fabry-Perot interferometers (FPI) for near infrared (NIR) wavelengths has led to the development of ultra-fast and low cost NIR sensors with potential to be used by the process industry. One of these miniaturised sensors operating from 1350 to 1650 nm, was integrated into a software platform to monitor a multiphase gas-liquid process for production of saturated polyester resins. Twelve batches were run in a two litre reactor mimicking industrial conditions (24 hr process, with temperatures ranging from 220-240 °C), using an immersion NIR transmission probe. Because of the multiphase nature of the reaction fluids strong interference produced by process disturbances such as temperature variations and the presence of solid particles and bubbles in the online spectra required a robust pre-processing algorithms and a good long-term stability of the probe. These allowed partial least squares (PLS) regression models to be built for the key analytical parameters acid number and viscosity. In parallel, spectra were also used to build an end-point detection model based on principal component analysis (PCA) for multivariate statistical process control (MSPC). The novel MEMS-FPI sensor combined with robust chemometric analysis proved to be a suitable and affordable alternative for online process monitoring, contributing to sustainability in the process industry.