Multivariate Statistical Process Control Process Monitoring Methods and Applications /

• Main Authors: Ge, Zhiqiang. (Author), Song, Zhihuan. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic
• Language: English
• Published: London : Springer London : Imprint: Springer, 2013.
• Series: Advances in Industrial Control,
• Subjects: Engineering.; Control.
• Online Access: https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-1-4471-4513-4

� Given their key position in the process control industry, process monitoring techniques have been extensively investigated by industrial practitioners and academic control researchers. Multivariate statistical process control (MSPC) is one of the most popular data-based methods for process monitor...

Table of Contents:

• Introduction
• An Overview of Conventional MSPC Methods
• Non-Gaussian Process Monitoring
• Fault Reconstruction and Identification
• Nonlinear Process Monitoring: Part I
• Nonlinear Process Monitoring: Part 2
• Time-varying Process Monitoring
• Multimode Process Monitoring: Part 1
• Multimode Process Monitoring: Part 2
• Dynamic Process Monitoring
• Probabilistic Process Monitoring
• Plant-wide Process Monitoring: Multiblock Method
• Reference
• Index.