Statistical Analysis Of Process Capability Indices With Measurement Errors

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Statistical Analysis Of Process Capability Indices With Measurement Errors

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Author : Silvano Bordignon
language : it
Publisher:
Release Date : 2001

Statistical Analysis Of Process Capability Indices With Measurement Errors written by Silvano Bordignon and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with categories.

Statistical Analysis Of Process Capability Indices With Measurement Errors

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Author : Silvano Bordignon
language : en
Publisher:
Release Date : 2001

Statistical Analysis Of Process Capability Indices With Measurement Errors written by Silvano Bordignon and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with categories.

Encyclopedia And Handbook Of Process Capability Indices

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Author : W. L. Pearn
language : en
Publisher:
Release Date : 2006

Encyclopedia And Handbook Of Process Capability Indices written by W. L. Pearn and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Process control categories.

1. The C[symbol] index. 1.1. Process precision and the C[symbol] index. 1.2. Estimating and testing C[symbol] based on a single sample. 1.3. Estimating and testing C[symbol] based on multiple samples. 1.4. Estimating and testing C[symbol] based on (X̄, R) control chart sample. 1.5. Estimating and testing C[symbol] based on (X̄, S) samples. 1.6. A Bayesian approach to assessment of C[symbol] -- 2. The C[symbol] index. 2.1. Process accuracy and the C[symbol] index. 2.2. Estimating and testing C[symbol] based on a single sample. 2.3. Estimating and testing C[symbol] based on multiple samples. 2.4. Bayesian-like estimator of C[symbol] -- 3. The C[symbol] index. 3.1. Process capability and the C[symbol] index. 3.2. Estimating and testing C[symbol] based on a single sample. 3.3. Estimating and testing C[symbol] based on multiple samples. 3.4. The Bayesian approach to C[symbol]. 3.5. The Bayesian-like estimator of C[symbol] -- 4. The C[symbol] index. 4.1. Process capability and the C[symbol] index. 4.2. Estimating and testing C[symbol] based on one single sample. 4.3. Estimating and testing C[symbol] based on multiple samples. 4.4. The Bayesian approach to C[symbol] -- 5. The loss indices. 5.1. Process loss and the L[symbol] index. 5.2. Estimation of L[symbol], L[symbol], and L[symbol]. 5.3. Upper confidence bounds of L[symbol], L[symbol], and L[symbol]. 5.4. Testing process capability based on the process loss -- 6. The C[symbol] index. 6.1. Process capability and the C[symbol] index. 6.2. Estimating and testing C[symbol] based on a single sample. 6.3. Estimating and testing C[symbol] based on multiple samples. 6.4. Bayesian-like estimation of C[symbol] -- 7. The S[symbol] index 7.1. Process capability and the S[symbol] index. 7.2. Estimating and testing S[symbol] based on a single sample. 7.3. Hypothesis testing with S[symbol] -- 8. The C[symbol]/C[symbol] index. 8.1. Process capability and the index C[symbol]/C[symbol]. 8.2. Estimating and testing C[symbol]/C[symbol]: based on single sample. 8.3. Estimating and testing C[symbol]/C[symbol]: based on multiple samples. 8.4. Estimating and testing C[symbol]/C[symbol]: Bayesian approach with single sample -- 9. Multi-Process Performance Analysis Chart (MPPAC). 9.1. Introduction. 9.2. The modified C[symbol] MPPAC. 9.3. The C[symbol] MPPAC. 9.4. The S[symbol] MPPAC. 9.5. The L[symbol] MPPAC -- 10. PCIs with asymmetric specification limits. 10.1. Introduction. 10.2. The C[symbol] index for asymmetric tolerances. 10.3. The C[symbol] index for asymmetric tolerances. 10.4. The C[symbol] index for asymmetric tolerances. 10.5. The C[symbol] index for asymmetric tolerances. 10.6. The loss index for asymmetric tolerances -- 11. Supplier selection based on PCIs. 11.1. Introduction. 11.2. Tseng and Wu's MLR selection rule based on C[symbol]. 11.3. Chou's approximate selection rule based on C[symbol] and C[symbol]. 11.4. Huang and Lee's approximate selection rule based on C[symbol] -- 12. Acceptance sampling plans based on PCIs. 12.1. Introduction. 12.2. Acceptance sampling plans based on C[symbol]. 12.3. Acceptance sampling plans based on C[symbol]. 12.4. Acceptance sampling plans based on C[symbol]. 12.5. Acceptance sampling plans based on C[symbol] and C[symbol] -- 13. Process capability measures in presence of gauge measurement errors. 13.1. Introduction. 13.2. Estimating and testing C[symbol] in presence of gauge measurement errors. 13.3. Estimating and testing C[symbol] in presence of gauge. 13.4. Estimating and testing C[symbol] in presence of gauge. 13.5. Estimating and testing C[symbol] in presence of gauge measurement errors. 13.6. Estimating and testing C[symbol] and C[symbol] in presence of gauge measurement errors -- 14. Process capability assessment with tool wear. 14.1. Introduction. 14.2. A review of various approaches -- 15. Process capability assessment for non-normal processes. 15.1. Introduction. 15.2. A brief review of various approaches -- 16. Multivariate process capability indices

Handbook Of Multivariate Process Capability Indices

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Author : Ashis Kumar Chakraborty
language : en
Publisher: CRC Press
Release Date : 2021-01-20

Handbook Of Multivariate Process Capability Indices written by Ashis Kumar Chakraborty and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-20 with Business & Economics categories.

Providing a single-valued assessment of the performance of a process is often one of the greatest challenges for a quality professional. Process Capability Indices (PCIs) precisely do this job. For processes having a single measurable quality characteristic, there is an ample number of PCIs, defined in literature. The situation worsens for multivariate processes, i.e., where there is more than one correlated quality characteristic. Since in most situations quality professionals face multiple quality characteristics to be controlled through a process, Multivariate Process Capability Indices (MPCIs) become the order of the day. However, there is no book which addresses and explains different MPCIs and their properties. The literature of Multivariate Process Capability Indices (MPCIs) is not well organized, in the sense that a thorough and systematic discussion on the various MPCIs is hardly available in the literature. Handbook of Multivariate Process Capability Indices provides an extensive study of the MPCIs defined for various types of specification regions. This book is intended to help quality professionals to understand which MPCI should be used and in what situation. For researchers in this field, the book provides a thorough discussion about each of the MPCIs developed to date, along with their statistical and analytical properties. Also, real life examples are provided for almost all the MPCIs discussed in the book. This helps both the researchers and the quality professionals alike to have a better understanding of the MPCIs, which otherwise become difficult to understand, since there is more than one quality characteristic to be controlled at a time. Features: A complete guide for quality professionals on the usage of different MPCIs. A step by step discussion on multivariate process capability analysis, starting from a brief discussion on univariate indices. A single source for all kinds of MPCIs developed so far. Comprehensive analysis of the MPCIs, including analysis of real-life data. References provided at the end of each chapter encompass the entire literature available on the respective topic. Interpretation of the MPCIs and development of threshold values of many MPCIs are also included. This reference book is aimed at the post graduate students in Industrial Statistics. It will also serve researchers working in the field of Industrial Statistics, as well as practitioners requiring thorough guidance regarding selection of an appropriate MPCI suitable for the problem at hand.

Six Sigma And Beyond

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Author : D.H. Stamatis
language : en
Publisher: CRC Press
Release Date : 2002-09-25

Six Sigma And Beyond written by D.H. Stamatis and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-09-25 with Business & Economics categories.

In this volume of the Six Sigma and Beyond series, quality engineering expert D.H. Stamatis focuses on how Statistical Process Control (SPC) relates to Six Sigma. He emphasizes the "why we do" and "how to do" SPC in many different environments. The book provides readers with an overview of SPC in easy-to-follow, easy-to-understand terms. The author reviews and explains traditional SPC tools and how they relate to Six Sigma and goes on to cover the use of advanced techniques. In addition, he addresses issues that concern service SPC and short run processes, explores the issue of capability for both the short run and the long run, and discusses topics in measurement.

Process Capability Analysis

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Author : Neil W. Polhemus
language : en
Publisher: CRC Press
Release Date : 2017-11-22

Process Capability Analysis written by Neil W. Polhemus and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-22 with Business & Economics categories.

Process Capability Analysis: Estimating Quality presents a systematic exploration of process capability analysis and how it may be used to estimate quality. The book is designed for practitioners who are tasked with insuring a high level of quality for the products and services offered by their organizations. Along with describing the necessary statistical theory, the book illustrates the practical application of the techniques to data that do not always satisfy the standard assumptions. The first two chapters deal with attribute data, where the estimation of quality is restricted to counts of nonconformities. Both classical and Bayesian methods are discussed. The rest of the book deals with variable data, including extensive discussions of both capability indices and statistical tolerance limits. Considerable emphasis is placed on methods for handling non-normal data. Also included are discussions of topics often omitted in discussions of process capability, including multivariate capability indices, multivariate tolerance limits, and capability control charts. A separate chapter deals with the problem of determining adequate sample sizes for estimating process capability. Features:  Comprehensive treatment of the subject with consistent theme of estimating percent of nonconforming product or service.  Includes Bayesian methods.  Extension of univariate techniques to multivariate data.  Demonstration of all techniques using Statgraphics data analysis software. Neil Polhemus is Chief Technology Officer at Statgraphics Technology and the original developer of the Statgraphics program for statistical analysis and data visualization. Dr. Polhemus spent 6 years on the faculty of the School of Engineering and Applied Science at Princeton University before moving full-time to software development and consulting. He has taught courses dealing with statistical process control, design of experiments and data analysis for more than 100 companies and government agencies.

Statistical Evaluation And Analysis Of Form And Profile Errors Based On Discrete Measurement Data Form Errors

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Author : SUNG HO CHANG
language : en
Publisher:
Release Date : 1991

Statistical Evaluation And Analysis Of Form And Profile Errors Based On Discrete Measurement Data Form Errors written by SUNG HO CHANG and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with categories.

approximations. The proposed sample sizes and estimating methods are verified by a simulation study and case studies of real part measurements.

Statistical Methods For Quality Assurance

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Author : Stephen B. Vardeman
language : en
Publisher: Springer
Release Date : 2016-08-26

Statistical Methods For Quality Assurance written by Stephen B. Vardeman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-26 with Mathematics categories.

This undergraduate statistical quality assurance textbook clearly shows with real projects, cases and data sets how statistical quality control tools are used in practice. Among the topics covered is a practical evaluation of measurement effectiveness for both continuous and discrete data. Gauge Reproducibility and Repeatability methodology (including confidence intervals for Repeatability, Reproducibility and the Gauge Capability Ratio) is thoroughly developed. Process capability indices and corresponding confidence intervals are also explained. In addition to process monitoring techniques, experimental design and analysis for process improvement are carefully presented. Factorial and Fractional Factorial arrangements of treatments and Response Surface methods are covered. Integrated throughout the book are rich sets of examples and problems that help readers gain a better understanding of where and how to apply statistical quality control tools. These large and realistic problem sets in combination with the streamlined approach of the text and extensive supporting material facilitate reader understanding. Second Edition Improvements Extensive coverage of measurement quality evaluation (in addition to ANOVA Gauge R&R methodologies) New end-of-section exercises and revised-end-of-chapter exercises Two full sets of slides, one with audio to assist student preparation outside-of-class and another appropriate for professors’ lectures Substantial supporting material Supporting Material Seven R programs that support variables and attributes control chart construction and analyses, Gauge R&R methods, analyses of Fractional Factorial studies, Propagation of Error analyses and Response Surface analyses Documentation for the R programs Excel data files associated with the end-of-chapter problem sets, most from real engineering settings

Process Capability Indices

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Author : Samuel Kotz
language : en
Publisher: Routledge
Release Date : 2017-10-19

Process Capability Indices written by Samuel Kotz and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-19 with Business & Economics categories.

A solid, rigorous, yet comprehensible analysis of process capability indices, this work bridges the gap between theoretical statisticians and quality control practitioners, showing how an understanding of these indices can lead to process improvement.

Handbook Of Multivariate Process Capability Indices

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Author : Ashis Kumar Chakraborty
language : en
Publisher: CRC Press
Release Date : 2021-01-06

Handbook Of Multivariate Process Capability Indices written by Ashis Kumar Chakraborty and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-06 with Business & Economics categories.

Providing a single-valued assessment of the performance of a process is often one of the greatest challenges for a quality professional. Process Capability Indices (PCIs) precisely do this job. For processes having a single measurable quality characteristic, there is an ample number of PCIs, defined in literature. The situation worsens for multivariate processes, i.e., where there is more than one correlated quality characteristic. Since in most situations quality professionals face multiple quality characteristics to be controlled through a process, Multivariate Process Capability Indices (MPCIs) become the order of the day. However, there is no book which addresses and explains different MPCIs and their properties. The literature of Multivariate Process Capability Indices (MPCIs) is not well organized, in the sense that a thorough and systematic discussion on the various MPCIs is hardly available in the literature. Handbook of Multivariate Process Capability Indices provides an extensive study of the MPCIs defined for various types of specification regions. This book is intended to help quality professionals to understand which MPCI should be used and in what situation. For researchers in this field, the book provides a thorough discussion about each of the MPCIs developed to date, along with their statistical and analytical properties. Also, real life examples are provided for almost all the MPCIs discussed in the book. This helps both the researchers and the quality professionals alike to have a better understanding of the MPCIs, which otherwise become difficult to understand, since there is more than one quality characteristic to be controlled at a time. Features: A complete guide for quality professionals on the usage of different MPCIs. A step by step discussion on multivariate process capability analysis, starting from a brief discussion on univariate indices. A single source for all kinds of MPCIs developed so far. Comprehensive analysis of the MPCIs, including analysis of real-life data. References provided at the end of each chapter encompass the entire literature available on the respective topic. Interpretation of the MPCIs and development of threshold values of many MPCIs are also included. This reference book is aimed at the post graduate students in Industrial Statistics. It will also serve researchers working in the field of Industrial Statistics, as well as practitioners requiring thorough guidance regarding selection of an appropriate MPCI suitable for the problem at hand.