Divide et impera: How disentangling common and distinctive variability in multiset data analysis can aid industrial process troubleshooting and understanding

The possibility of addressing the problem of process troubleshooting and understanding by modelling common and distinctive sources of variation (factors or components) underlying two sets of measurements was explored in a real-world industrial case study. The used strategy includes a novel approach to systematically detect the number of common and distinctive components. An extension of this strategy for the analysis of a larger number of data blocks, which allows the comparison of data from multiple processing units, is also discussed.