| Description |
1 online resource |
| Series |
Advances in industrial control, 1430-9491 |
|
Advances in industrial control.
|
| Contents |
Introduction -- An Overview of Conventional MSPC Methods -- Non-Gaussian Process Monitoring -- Fault Reconstruction and Identification -- Nonlinear Process Monitoring: Part 1 -- 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 |
| Summary |
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 monitoring and is widely used in various industrial areas. Effective routines for process monitoring can help operators run industrial processes efficiently at the same time as maintaining high product quality |
| Analysis |
Engineering |
|
Control |
| Bibliography |
Includes bibliographical references and index |
| Subject |
Process control -- Statistical methods.
|
|
Multivariate analysis.
|
| Form |
Electronic book
|
| Author |
Song, Zhihuan.
|
| LC no. |
2012947424 |
| ISBN |
1283910624 (MyiLibrary) |
|
1447145127 (hbk.) |
|
1447145135 (electronic bk.) |
|
9781283910620 (MyiLibrary) |
|
9781447145127 (hbk.) |
|
9781447145134 (electronic bk.) |
|
