SWiVIA - Sliding window variographic image analysis for real-time assessment of heterogeneity indices in blending processes monitored with hyperspectral imaging

Abstract

Controlling blending processes of solid material using advanced real-time sensing technologies tools is crucial to guarantee the quality attributes of manufactured products from diverse industries. The use of process analytical technology (PAT) tools based on chemical imaging systems are useful to assess heterogeneity information during mixing processes. Recently, a powerful procedure for heterogeneity assessment based on the combination of off-line acquired chemical images and variographic analysis has been proposed to provide specific heterogeneity indices related to global and distributional heterogeneity. This work proposes a novel PAT tool combining in situ chemical imaging and variogram-derived quantitative heterogeneity indices for the real-time monitoring of blending processes. The proposed method, so called sliding window variographic image analysis (SWiVIA), derives heterogeneity indices in real-time associated with a sliding image window that moves continuously until the full blending time interval is covered. The SWiVIA method is thoroughly assessed paying attention at the effect of relevant factors for continuous blending monitoring and heterogeneity description, such as the scale of scrutiny needed for heterogeneity definition or the blending period defined to set the sliding image window. SWiVIA is tested on blending runs of pharmaceutical and food products monitored with an in situ near-infrared chemical imaging system. The results obtained help to detect abnormal mixing phenomena and can be the basis to establish blending process control indicators in the future. SWiVIA is adapted to study blending behaviors of the bulk product or compound-specific blending evolutions.

Keywords: Blending; Heterogeneity indices; Hyperspectral imaging; Variographic analysis.