Batch Processes

An overview of the fundamental principles of batch processes for novice and experienced professionals in chemical, biotech, and pharmaceutical industries.

Process Analytical Technologies (PAT) have become increasingly important with the establishment of the quality-by-design approach in industrial processes. Methods based on the projection to latent structures, often referred to as chemometric methods, are a main component of PAT. When used alongside multivariate statistical process control (MSPC), these methods enable the timely detection of process abnormalities. Furthermore, process understanding can be improved by applying latent structures-based (LSB) methods. This is especially true in batch processes, where the inherent complexity of the model results in a high degree of uncertainty in the operation. Batch processes are of paramount importance in various industrial sectors, including chemical, biotech and pharmaceutical industries.

Batch Processes: Monitoring and Process Understanding offers a comprehensive examination of batch process modeling, monitoring, and control, emphasizing PAT and LSB methods such as principal component analysis (PCA) and partial least squares (PLS).

Batch Processes: Monitoring and Process Understanding addresses practical challenges in batch data analysis, such as preprocessing, missing data imputation, equalization, synchronization (DTW, RGTW, Multisynchro), and multi-phase modeling. Real-world case studies and hands-on MATLAB examples using the MVBatch toolbox bridge theory and practice, demonstrating how LSB methods improve quality, safety, and economic and ecological outcomes across chemical, biotech, and pharmaceutical industries.

Batch Processes: Monitoring and Process Understanding is an essential guide for professionals in chemical, biotech and pharmaceutical industries seeking both foundational knowledge and advanced techniques in batch processes and data analysis.