Batch Processes
Monitoring and Process Understanding
Batch Processes
Monitoring and Process Understanding
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.
Prologue: Challenges for the third millennium
Prologue: Challenges for the third millennium
1 Introduction
1.1 Industrial batch processes
1.2 Types of sensors
1.3 Batch process modeling
1.4 Bilinear modeling cycle for batch process monitoring
2 Data-driven models based on latent variables
2.1 Compression
2.2 Principal components analysis
2.3 Regression
2.4 Regression models based on latent variables
2.5 Multivariate Exploratory Data Analysis
2.6 Missing data
3 Batch data equalization
3.1 Introduction
3.2 Challenges in batch equalization
3.3 Equalization of variables within a batch
3.4 Multi-rate system
4 Batch synchronization
4.1 Introduction
4.2 Synchronization approaches
4.3 Effect of synchronization on the correlation structure
5 Batch data preprocessing
5.1 Batch preprocessing operations
5.2 Mean centering
5.3 Scaling
6 Three-way to two-way transformation
6.1 Introduction
6.2 Single-model approach
6.3 K-models approach
6.4 Multi-phase Approach
6.5 Conclusions
7 Batch Process Data Analysis and Statistical Monitoring
7.1 Introduction
7.2 Historical Batch Data Analysis
7.3 Batch Multivariate Statistical Process Control (BMSPC)
7.4 Practical issues
González-Martínez, José M.
Camacho, José
Borràs-Ferrís, Joan
Ferrer, Alberto
| ISBN | 9783527326402 |
|---|---|
| Article number | 9783527326402 |
| Media type | Book |
| Edition number | 1. Auflage |
| Copyright year | 2026 |
| Publisher | Wiley-VCH GmbH Wiley-VCH GmbH, Boschstrasse 12, DE-69469 Weinheim |
| Length | 256 pages |
| Illustrations | 300 SW-Abb., 7 Farbabb. |
| Language | English |
