Multivariate Statistical Process Control With Industrial Applications
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Multivariate Statistical Process Control With Industrial Applications
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Author : Robert L. Mason
language : en
Publisher: SIAM
Release Date : 2002-01-01
Multivariate Statistical Process Control With Industrial Applications written by Robert L. Mason and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-01-01 with Technology & Engineering categories.
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 Process Control
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Author : Zhiqiang Ge
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-11-28
Multivariate Statistical Process Control written by Zhiqiang Ge and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-28 with Technology & Engineering categories.
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.
Statistical Monitoring Of Complex Multivatiate Processes
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Author : Uwe Kruger
language : en
Publisher: John Wiley & Sons
Release Date : 2012-08-06
Statistical Monitoring Of Complex Multivatiate Processes written by Uwe Kruger and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-06 with Mathematics categories.
The development and application of multivariate statisticaltechniques in process monitoring has gained substantial interestover the past two decades in academia and industry alike. Initially developed for monitoring and fault diagnosis in complexsystems, such techniques have been refined and applied in variousengineering areas, for example mechanical and manufacturing,chemical, electrical and electronic, and power engineering. The recipe for the tremendous interest in multivariate statisticaltechniques lies in its simplicity and adaptability for developingmonitoring applications. In contrast, competitive model,signal or knowledge based techniques showed their potential onlywhenever cost-benefit economics have justified the required effortin developing applications. Statistical Monitoring of Complex Multivariate Processespresents recent advances in statistics based process monitoring,explaining how these processes can now be used in areas such asmechanical and manufacturing engineering for example, in additionto the traditional chemical industry. This book: Contains a detailed theoretical background of the componenttechnology. Brings together a large body of work to address thefield’s drawbacks, and develops methods for theirimprovement. Details cross-disciplinary utilization, exemplified by examplesin chemical, mechanical and manufacturing engineering. Presents real life industrial applications, outliningdeficiencies in the methodology and how to address them. Includes numerous examples, tutorial questions and homeworkassignments in the form of individual and team-based projects, toenhance the learning experience. Features a supplementary website including Matlab algorithmsand data sets. This book provides a timely reference text to the rapidlyevolving area of multivariate statistical analysis for academics,advanced level students, and practitioners alike.
Statistical Monitoring Of Complex Multivatiate Processes
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Author : Uwe Kruger
language : en
Publisher: John Wiley & Sons
Release Date : 2012-10-04
Statistical Monitoring Of Complex Multivatiate Processes written by Uwe Kruger and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-04 with Mathematics categories.
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 contrast, competitive model, signal or knowledge based techniques showed their potential only whenever cost-benefit economics have justified the required effort in developing applications. Statistical Monitoring of Complex Multivariate Processes presents recent advances in statistics based process monitoring, explaining how these processes can now be used in areas such as mechanical and manufacturing engineering for example, in addition to the traditional chemical industry. This book: Contains a detailed theoretical background of the component technology. Brings together a large body of work to address the field’s drawbacks, and develops methods for their improvement. Details cross-disciplinary utilization, exemplified by examples in chemical, mechanical and manufacturing engineering. Presents real life industrial applications, outlining deficiencies in the methodology and how to address them. Includes numerous examples, tutorial questions and homework assignments in the form of individual and team-based projects, to enhance the learning experience. Features a supplementary website including Matlab algorithms and data sets. This book provides a timely reference text to the rapidly evolving area of multivariate statistical analysis for academics, advanced level students, and practitioners alike.
Multivariate Statistical Quality Control Using R
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Author : Edgar Santos-Fernández
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-09-22
Multivariate Statistical Quality Control Using R written by Edgar Santos-Fernández and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-22 with Business & Economics categories.
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
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Author : Camil Fuchs
language : en
Publisher: CRC Press
Release Date : 1998-04-22
Multivariate Quality Control written by Camil Fuchs and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-04-22 with Business & Economics categories.
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
Statistical Process Control For Real World Applications
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Author : William A. Levinson
language : en
Publisher: CRC Press
Release Date : 2010-12-21
Statistical Process Control For Real World Applications written by William A. Levinson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-12-21 with Business & Economics categories.
The normal or bell curve distribution is far more common in statistics textbooks than it is in real factories, where processes follow non-normal and often highly skewed distributions. Statistical Process Control for Real-World Applications shows how to handle non-normal applications scientifically and explain the methodology to suppliers and custom
Introduction To Statistical Process Control
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Author : Peihua Qiu
language : en
Publisher: CRC Press
Release Date : 2013-10-14
Introduction To Statistical Process Control written by Peihua Qiu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-14 with Business & Economics categories.
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
Modern Industrial Statistics
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Author : Ron S. Kenett
language : en
Publisher: John Wiley & Sons
Release Date : 2014-01-28
Modern Industrial Statistics written by Ron S. Kenett and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-28 with Mathematics categories.
Fully revised and updated, this book combines a theoretical background with examples and references to R, MINITAB and JMP, enabling practitioners to find state-of-the-art material on both foundation and implementation tools to support their work. Topics addressed include computer-intensive data analysis, acceptance sampling, univariate and multivariate statistical process control, design of experiments, quality by design, and reliability using classical and Bayesian methods. The book can be used for workshops or courses on acceptance sampling, statistical process control, design of experiments, and reliability. Graduate and post-graduate students in the areas of statistical quality and engineering, as well as industrial statisticians, researchers and practitioners in these fields will all benefit from the comprehensive combination of theoretical and practical information provided in this single volume. Modern Industrial Statistics: With applications in R, MINITAB and JMP: Combines a practical approach with theoretical foundations and computational support. Provides examples in R using a dedicated package called MISTAT, and also refers to MINITAB and JMP. Includes exercises at the end of each chapter to aid learning and test knowledge. Provides over 40 data sets representing real-life case studies. Is complemented by a comprehensive website providing an introduction to R, and installations of JMP scripts and MINITAB macros, including effective tutorials with introductory material: www.wiley.com/go/modern_industrial_statistics.
Modern Industrial Statistics
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Author : Ron S. Kenett
language : en
Publisher: John Wiley & Sons
Release Date : 2021-05-18
Modern Industrial Statistics written by Ron S. Kenett and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-18 with Mathematics categories.
Modern Industrial Statistics The new edition of the prime reference on the tools of statistics used in industry and services, integrating theoretical, practical, and computer-based approaches Modern Industrial Statistics is a leading reference and guide to the statistics tools widely used in industry and services. Designed to help professionals and students easily access relevant theoretical and practical information in a single volume, this standard resource employs a computer-intensive approach to industrial statistics and provides numerous examples and procedures in the popular R language and for MINITAB and JMP statistical analysis software. Divided into two parts, the text covers the principles of statistical thinking and analysis, bootstrapping, predictive analytics, Bayesian inference, time series analysis, acceptance sampling, statistical process control, design and analysis of experiments, simulation and computer experiments, and reliability and survival analysis. Part A, on computer age statistical analysis, can be used in general courses on analytics and statistics. Part B is focused on industrial statistics applications. The fully revised third edition covers the latest techniques in R, MINITAB and JMP, and features brand-new coverage of time series analysis, predictive analytics and Bayesian inference. New and expanded simulation activities, examples, and case studies—drawn from the electronics, metal work, pharmaceutical, and financial industries—are complemented by additional computer and modeling methods. Helping readers develop skills for modeling data and designing experiments, this comprehensive volume: Explains the use of computer-based methods such as bootstrapping and data visualization Covers nonstandard techniques and applications of industrial statistical process control (SPC) charts Contains numerous problems, exercises, and data sets representing real-life case studies of statistical work in various business and industry settings Includes access to a companion website that contains an introduction to R, sample R code, csv files of all data sets, JMP add-ins, and downloadable appendices Provides an author-created R package, mistat, that includes all data sets and statistical analysis applications used in the book Part of the acclaimed Statistics in Practice series, Modern Industrial Statistics with Applications in R, MINITAB, and JMP, Third Edition, is the perfect textbook for advanced undergraduate and postgraduate courses in the areas of industrial statistics, quality and reliability engineering, and an important reference for industrial statisticians, researchers, and practitioners in related fields. The mistat R-package is available from the R CRAN repository.