Multivariate Statistical Process Control (2020-EU-EPO-461)
Jan 30, 2020 8:00 AM
| Last Modified: Feb 23, 2020 12:26 PM
Piet Hoogkamer, Principal Scientist, Abbott Established Pharmaceuticals Sven Daniel Schmitz, TBA, Abbott Established Pharmaceuticals
At Abbott, statistical process control (SPC) has been around for some time to better understand, control and improve our various manufacturing processes. Having said that, often this is still equivalent to univariate control charts tracking observations in one dimension. With the quality attributes of our processes being multivariate in nature and the increasing availability of more and different types of data, e.g. spectra, the use of multivariate statistical process control (MSPC) becomes increasingly attractive or even mandatory.
Inspired by the EDQM draft chapter (5.28) on MSPC, we will showcase the use of multivariate statistical process control (MSPC) to analyze 2 sets of highly complex and (auto)correlated example data. One, on controlling dissolution behavior via the particle size distribution, the second, on monitoring the state of a process by using all available measurements.