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Multivariate Statistical Process Control

Author: Zhiqiang Ge

Publisher: Springer Science & Business Media

Published: 2012-11-28

Total Pages: 204

ISBN-13: 1447145135

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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. Multivariate Statistical Process Control reviews the developments and improvements that have been made to MSPC over the last decade, and goes on to propose a series of new MSPC-based approaches for complex process monitoring. These new methods are demonstrated in several case studies from the chemical, biological, and semiconductor industrial areas. Control and process engineers, and academic researchers in the process monitoring, process control and fault detection and isolation (FDI) disciplines will be interested in this book. It can also be used to provide supplementary material and industrial insight for graduate and advanced undergraduate students, and graduate engineers. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.

Book Synopsis Multivariate Statistical Process Control by : Zhiqiang Ge

Download or read book Multivariate Statistical Process Control written by Zhiqiang Ge and published by Springer Science & Business Media. This book was released on 2012-11-28 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Multivariate Statistical Process Control reviews the developments and improvements that have been made to MSPC over the last decade, and goes on to propose a series of new MSPC-based approaches for complex process monitoring. These new methods are demonstrated in several case studies from the chemical, biological, and semiconductor industrial areas. Control and process engineers, and academic researchers in the process monitoring, process control and fault detection and isolation (FDI) disciplines will be interested in this book. It can also be used to provide supplementary material and industrial insight for graduate and advanced undergraduate students, and graduate engineers. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.

Multivariate Statistical Process Control with Industrial Applications

Author: Robert L. Mason

Publisher: SIAM

Published: 2002-01-01

Total Pages: 271

ISBN-13: 0898714966

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Detailed coverage of the practical aspects of multivariate statistical process control (MVSPC) based on the application of Hotelling's T2 statistic. MVSPC is the application of multivariate statistical techniques to improve the quality and productivity of an industrial process. Provides valuable insight into the T2 statistic.

Book Synopsis Multivariate Statistical Process Control with Industrial Applications by : Robert L. Mason

Download or read book Multivariate Statistical Process Control with Industrial Applications written by Robert L. Mason and published by SIAM. This book was released on 2002-01-01 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: Detailed coverage of the practical aspects of multivariate statistical process control (MVSPC) based on the application of Hotelling's T2 statistic. MVSPC is the application of multivariate statistical techniques to improve the quality and productivity of an industrial process. Provides valuable insight into the T2 statistic.

Multivariate Statistical Quality Control Using R

Author: Edgar Santos-Fernández

Publisher: Springer Science & Business Media

Published: 2012-09-22

Total Pages: 134

ISBN-13: 1461454522

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The intensive use of automatic data acquisition system and the use of cloud computing for process monitoring have led to an increased occurrence of industrial processes that utilize statistical process control and capability analysis. These analyses are performed almost exclusively with multivariate methodologies. The aim of this Brief is to present the most important MSQC techniques developed in R language. The book is divided into two parts. The first part contains the basic R elements, an introduction to statistical procedures, and the main aspects related to Statistical Quality Control (SQC). The second part covers the construction of multivariate control charts, the calculation of Multivariate Capability Indices.

Book Synopsis Multivariate Statistical Quality Control Using R by : Edgar Santos-Fernández

Download or read book Multivariate Statistical Quality Control Using R written by Edgar Santos-Fernández and published by Springer Science & Business Media. This book was released on 2012-09-22 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: The intensive use of automatic data acquisition system and the use of cloud computing for process monitoring have led to an increased occurrence of industrial processes that utilize statistical process control and capability analysis. These analyses are performed almost exclusively with multivariate methodologies. The aim of this Brief is to present the most important MSQC techniques developed in R language. The book is divided into two parts. The first part contains the basic R elements, an introduction to statistical procedures, and the main aspects related to Statistical Quality Control (SQC). The second part covers the construction of multivariate control charts, the calculation of Multivariate Capability Indices.

Multivariate Quality Control

Author: Camil Fuchs

Publisher: CRC Press

Published: 1998-04-22

Total Pages: 224

ISBN-13: 148227373X

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Provides a theoretical foundation as well as practical tools for the analysis of multivariate data, using case studies and MINITAB computer macros to illustrate basic and advanced quality control methods. This work offers an approach to quality control that relies on statistical tolerance regions, and discusses computer graphic analysis highlightin

Book Synopsis Multivariate Quality Control by : Camil Fuchs

Download or read book Multivariate Quality Control written by Camil Fuchs and published by CRC Press. This book was released on 1998-04-22 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a theoretical foundation as well as practical tools for the analysis of multivariate data, using case studies and MINITAB computer macros to illustrate basic and advanced quality control methods. This work offers an approach to quality control that relies on statistical tolerance regions, and discusses computer graphic analysis highlightin

Introduction to Statistical Process Control

Author: Peihua Qiu

Publisher: CRC Press

Published: 2013-10-14

Total Pages: 520

ISBN-13: 1482220415

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A major tool for quality control and management, statistical process control (SPC) monitors sequential processes, such as production lines and Internet traffic, to ensure that they work stably and satisfactorily. Along with covering traditional methods, Introduction to Statistical Process Control describes many recent SPC methods that improve upon

Book Synopsis Introduction to Statistical Process Control by : Peihua Qiu

Download or read book Introduction to Statistical Process Control written by Peihua Qiu and published by CRC Press. This book was released on 2013-10-14 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: A major tool for quality control and management, statistical process control (SPC) monitors sequential processes, such as production lines and Internet traffic, to ensure that they work stably and satisfactorily. Along with covering traditional methods, Introduction to Statistical Process Control describes many recent SPC methods that improve upon

Multivariate Analysis in the Pharmaceutical Industry

Author: Ana Patricia Ferreira

Publisher: Academic Press

Published: 2018-04-24

Total Pages: 464

ISBN-13: 012811066X

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Multivariate Analysis in the Pharmaceutical Industry provides industry practitioners with guidance on multivariate data methods and their applications over the lifecycle of a pharmaceutical product, from process development, to routine manufacturing, focusing on the challenges specific to each step. It includes an overview of regulatory guidance specific to the use of these methods, along with perspectives on the applications of these methods that allow for testing, monitoring and controlling products and processes. The book seeks to put multivariate analysis into a pharmaceutical context for the benefit of pharmaceutical practitioners, potential practitioners, managers and regulators. Users will find a resources that addresses an unmet need on how pharmaceutical industry professionals can extract value from data that is routinely collected on products and processes, especially as these techniques become more widely used, and ultimately, expected by regulators. Targets pharmaceutical industry practitioners and regulatory staff by addressing industry specific challenges Includes case studies from different pharmaceutical companies and across product lifecycle of to introduce readers to the breadth of applications Contains information on the current regulatory framework which will shape how multivariate analysis (MVA) is used in years to come

Book Synopsis Multivariate Analysis in the Pharmaceutical Industry by : Ana Patricia Ferreira

Download or read book Multivariate Analysis in the Pharmaceutical Industry written by Ana Patricia Ferreira and published by Academic Press. This book was released on 2018-04-24 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate Analysis in the Pharmaceutical Industry provides industry practitioners with guidance on multivariate data methods and their applications over the lifecycle of a pharmaceutical product, from process development, to routine manufacturing, focusing on the challenges specific to each step. It includes an overview of regulatory guidance specific to the use of these methods, along with perspectives on the applications of these methods that allow for testing, monitoring and controlling products and processes. The book seeks to put multivariate analysis into a pharmaceutical context for the benefit of pharmaceutical practitioners, potential practitioners, managers and regulators. Users will find a resources that addresses an unmet need on how pharmaceutical industry professionals can extract value from data that is routinely collected on products and processes, especially as these techniques become more widely used, and ultimately, expected by regulators. Targets pharmaceutical industry practitioners and regulatory staff by addressing industry specific challenges Includes case studies from different pharmaceutical companies and across product lifecycle of to introduce readers to the breadth of applications Contains information on the current regulatory framework which will shape how multivariate analysis (MVA) is used in years to come

Introduction to Statistical Process Control

Author: Muhammad Aslam

Publisher: John Wiley & Sons

Published: 2020-09-16

Total Pages: 288

ISBN-13: 1119528453

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An Introduction to the Fundamentals and History of Control Charts, Applications, and Guidelines for Implementation Introduction to Statistical Process Control examines various types of control charts that are typically used by engineering students and practitioners. This book helps readers develop a better understanding of the history, implementation, and use-cases. Students are presented with varying control chart techniques, information, and roadmaps to ensure their control charts are operating efficiently and producing specification-confirming products. This is the essential text on the theories and applications behind statistical methods and control procedures. This eight-chapter reference breaks information down into digestible sections and covers topics including: ● An introduction to the basics as well as a background of control charts ● Widely used and newly researched attributes of control charts, including guidelines for implementation ● The process capability index for both normal and non-normal distribution via the sampling of multiple dependent states ● An overview of attribute control charts based on memory statistics ● The development of control charts using EQMA statistics For a solid understanding of control methodologies and the basics of quality assurance, Introduction to Statistical Process Control is a definitive reference designed to be read by practitioners and students alike. It is an essential textbook for those who want to explore quality control and systems design.

Book Synopsis Introduction to Statistical Process Control by : Muhammad Aslam

Download or read book Introduction to Statistical Process Control written by Muhammad Aslam and published by John Wiley & Sons. This book was released on 2020-09-16 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to the Fundamentals and History of Control Charts, Applications, and Guidelines for Implementation Introduction to Statistical Process Control examines various types of control charts that are typically used by engineering students and practitioners. This book helps readers develop a better understanding of the history, implementation, and use-cases. Students are presented with varying control chart techniques, information, and roadmaps to ensure their control charts are operating efficiently and producing specification-confirming products. This is the essential text on the theories and applications behind statistical methods and control procedures. This eight-chapter reference breaks information down into digestible sections and covers topics including: ● An introduction to the basics as well as a background of control charts ● Widely used and newly researched attributes of control charts, including guidelines for implementation ● The process capability index for both normal and non-normal distribution via the sampling of multiple dependent states ● An overview of attribute control charts based on memory statistics ● The development of control charts using EQMA statistics For a solid understanding of control methodologies and the basics of quality assurance, Introduction to Statistical Process Control is a definitive reference designed to be read by practitioners and students alike. It is an essential textbook for those who want to explore quality control and systems design.

Statistical Process Control and Quality Improvement

Author: Gerald Smith

Publisher: Macmillan College

Published: 1995

Total Pages: 600

ISBN-13:

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Book Synopsis Statistical Process Control and Quality Improvement by : Gerald Smith

Download or read book Statistical Process Control and Quality Improvement written by Gerald Smith and published by Macmillan College. This book was released on 1995 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches

Author: Fouzi Harrou

Publisher: Elsevier

Published: 2020-07-03

Total Pages: 330

ISBN-13: 0128193662

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Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches tackles multivariate challenges in process monitoring by merging the advantages of univariate and traditional multivariate techniques to enhance their performance and widen their practical applicability. The book proceeds with merging the desirable properties of shallow learning approaches – such as a one-class support vector machine and k-nearest neighbours and unsupervised deep learning approaches – to develop more sophisticated and efficient monitoring techniques. Finally, the developed approaches are applied to monitor many processes, such as waste-water treatment plants, detection of obstacles in driving environments for autonomous robots and vehicles, robot swarm, chemical processes (continuous stirred tank reactor, plug flow rector, and distillation columns), ozone pollution, road traffic congestion, and solar photovoltaic systems. Uses a data-driven based approach to fault detection and attribution Provides an in-depth understanding of fault detection and attribution in complex and multivariate systems Familiarises you with the most suitable data-driven based techniques including multivariate statistical techniques and deep learning-based methods Includes case studies and comparison of different methods

Book Synopsis Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches by : Fouzi Harrou

Download or read book Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches written by Fouzi Harrou and published by Elsevier. This book was released on 2020-07-03 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches tackles multivariate challenges in process monitoring by merging the advantages of univariate and traditional multivariate techniques to enhance their performance and widen their practical applicability. The book proceeds with merging the desirable properties of shallow learning approaches – such as a one-class support vector machine and k-nearest neighbours and unsupervised deep learning approaches – to develop more sophisticated and efficient monitoring techniques. Finally, the developed approaches are applied to monitor many processes, such as waste-water treatment plants, detection of obstacles in driving environments for autonomous robots and vehicles, robot swarm, chemical processes (continuous stirred tank reactor, plug flow rector, and distillation columns), ozone pollution, road traffic congestion, and solar photovoltaic systems. Uses a data-driven based approach to fault detection and attribution Provides an in-depth understanding of fault detection and attribution in complex and multivariate systems Familiarises you with the most suitable data-driven based techniques including multivariate statistical techniques and deep learning-based methods Includes case studies and comparison of different methods

Multivariate Statistical Methods in Quality Management

Author: Kai Yang

Publisher: McGraw Hill Professional

Published: 2004-03-17

Total Pages: 318

ISBN-13: 0071501371

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Multivariate statistical methods are an essential component of quality engineering data analysis. This monograph provides a solid background in multivariate statistical fundamentals and details key multivariate statistical methods, including simple multivariate data graphical display and multivariate data stratification. * Graphical multivariate data display * Multivariate regression and path analysis * Multivariate process control charts * Six sigma and multivariate statistical methods

Book Synopsis Multivariate Statistical Methods in Quality Management by : Kai Yang

Download or read book Multivariate Statistical Methods in Quality Management written by Kai Yang and published by McGraw Hill Professional. This book was released on 2004-03-17 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate statistical methods are an essential component of quality engineering data analysis. This monograph provides a solid background in multivariate statistical fundamentals and details key multivariate statistical methods, including simple multivariate data graphical display and multivariate data stratification. * Graphical multivariate data display * Multivariate regression and path analysis * Multivariate process control charts * Six sigma and multivariate statistical methods