Soft Sensors (SSs) are inferential dynamical models employed in industries to perform
prediction of process hard-to-measure variables based on their relation with easily …

One of the obstacles to the wider practical use of the multisensor systems for gas and liquid
analysis—electronic noses and tongues, is the limited temporal validity of the multivariate …

Historical data collected from processes are readily available. This paper looks at recent
advances in the use of data-driven models built from such historical data for monitoring, fault …

In recent decades, with the rapid development of artificial intelligence, data mining, and
cloud computing, new chemometric methods have sprung up and become one of the fastest …

The introduction of the Quality-by-Design (QbD) initiative and of the Process Analytical
Technology (PAT) framework by the Food and Drug Administration has opened the route to …

Process analytical technology is an essential step forward in pharmaceutical industry. Real-
time analyzers will provide timely data on quality properties. This information combined with …

Batch processes in manufacturing industries often adapt new products to meet the changing
market demands. Dynamic modeling with limited data for new products may lead to …

Calibration transfer between near‐infrared (NIR) spectrometers is a subtle issue in
chemometrics and process industry. In fact, as even very similar instruments may generate …

In this work, a domain-adaption joint-Y partial least squares (JYPLS) is proposed to solve
the problem of transfer learning for end-product quality prediction of batch processes. The …

An industrial process may operate over a range of conditions to produce different grades of
product. With a data‐based model, as conditions change, a different process model must be …