Functional Principal Component Analysis (FPCA) is an important dimension reduction
technique to interpret the main modes of functional data variation in terms of a small set of …

Over the past decades, control charts, one of the essential tools in Statistical Process Control
(SPC), have been widely implemented in manufacturing industries as an effective approach …

To increase the monitoring performance of the batch process with serious nonlinearity,
uneven-length, and limited-data issues, a supervised transfer-learning based functional …

In chemical processes, products of different grades are often produced. Data measured in
each grade have different latent features. Multiple data sets can be measured corresponding …

Many industrial processes are equipped with a large number of sensors, which usually
generate multichannel high-dimensional profiles that can be used to monitor the health …

A quality-related fault monitoring method of multi-phase batch process based on multiway
weighted elastic network is proposed in this paper. Firstly, to make the phase division for …

Unfolding is a pretreating operation in most existing batch process modeling methods, but it
would destroy the essential structure of the raw data. Also, the number of estimated …

Conventional data-driven models for batch processes conduct unfolding operations and
neglect the continuous property. A novel soft sensor method is proposed based on the …

Batch processing is a widely utilized technique in the manufacturing of high-value products.
Traditional methods for quality assessment in batch processes often lead to productivity and …

Several local models are used to approximate the nonlinear and multiphase characteristics
of the batch process. Existing methods using phase partition and modeling can yield a …