Screen LibraryStatistical monitoring of complex multivariate processes with applications in industrial process control /
"The development and application of multivariate statistical techniques in process monitoring has gained substantial interest over the past two decades in academia and industry alike. Initially developed for monitoring and fault diagnosis in complex systems, such techniques have been refined an...
Saved in:
| Main Authors: | |
|---|---|
| Group Author: | |
| Published: |
|
| Literature type: | Electronic eBook |
| Language: | English |
| Series: |
Statistics in practice
|
| Subjects: | |
| Online Access: |
http://onlinelibrary.wiley.com/book/10.1002/9780470517253 |
| Summary: |
"The development and application of multivariate statistical techniques in process monitoring has gained substantial interest over the past two decades in academia and industry alike. Initially developed for monitoring and fault diagnosis in complex systems, such techniques have been refined and applied in various engineering areas, for example mechanical and manufacturing, chemical, electrical and electronic, and power engineering. The recipe for the tremendous interest in multivariate statistical techniques lies in its simplicity and adaptability for developing monitoring applications. In |
| Carrier Form: | 1 online resource (xxix, 437 p.) : ill. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: |
9780470517253 (electronic bk.) 0470517255 (electronic bk.) 9781118381267 (electronic bk.) 1118381262 (electronic bk.) 9780470517246 (electronic bk.) 0470517247 (electronic bk.) |
| Index Number: | QA278 |
| CLC: | O212.4 |
| Contents: | Machine generated contents note: Preface Introduction I Fundamentals of Multivariate Statistical Process Control 1 Motivation for Multivariate Statistical Process Control 1.1 Summary of Statistical Process Control 1.1.1 Roots and Evolution of Statistical Process Control 1.1.2 Principles of Statistical Process Control 1.1.3 Hypothesis Testing, Type I and II errors 1.2 Why Multivariate Statistical Process Control 1.2.1 Statistically Uncorrelated Variables 1.2.2 Perfectly Correlated Variables 1.2.3 Highly Correlated Variables 1.2.4 Type I and II Errors and Dimension Reduction 1.3 Tutorial Sessi |