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Statistical methods for quality improvement /
"Praise for the Second Edition"As a comprehensive statistics reference book for quality improvement, it certainly is one of the best books available."--TechnometricsThis new edition continues to provide the most current, proven statistical methods for quality control and quality impro...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken, N.J. :
Wiley,
2011.
|
| Edición: | 3rd ed. |
| Colección: | Wiley series in probability and statistics.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Ryan, Thomas P., |d 1945- | |
| 245 | 1 | 0 | |a Statistical methods for quality improvement / |c Thomas P. Ryan. |
| 250 | |a 3rd ed. | ||
| 260 | |a Hoboken, N.J. : |b Wiley, |c 2011. | ||
| 300 | |a 1 online resource (xxiv, 672 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Wiley series in probability and statistics | |
| 505 | 0 | |6 880-01 |a Frontmatter -- Fundamental Quality Improvement and Statistical Concepts. Introduction -- Basic Tools for Improving Quality -- Basic Concepts in Statistics and Probability -- Control Charts and Process Capability. Control Charts for Measurements with Subgrouping (for One Variable) -- Control Charts for Measurements without Subgrouping (for One Variable) -- Control Charts for Attributes -- Process Capability -- Alternatives to Shewhart Charts -- Multivariate Control Charts for Measurement and Attribute Data -- Miscellaneous Control Chart Topics -- Beyond Control Charts: Graphical and Statistical Methods. Graphical Methods -- Linear Regression -- Design of Experiments -- Contributions of Genichi Taguchi and Alternative Approaches -- Evolutionary Operation -- Analysis of Means -- Using Combinations of Quality Improvement Tools -- Answers to Selected Exercises -- Appendix: Statistical Tables -- Author Index -- Subject Index -- Wiley Series in Probability and Statistics. | |
| 520 | |a "Praise for the Second Edition"As a comprehensive statistics reference book for quality improvement, it certainly is one of the best books available."--TechnometricsThis new edition continues to provide the most current, proven statistical methods for quality control and quality improvementThe use of quantitative methods offers numerous benefits in the fields of industry and business, both through identifying existing trouble spots and alerting management and technical personnel to potential problems. Statistical Methods for Quality Improvement, Third Edition guides readers through a broad range of tools and techniques that make it possible to quickly identify and resolve both current and potential trouble spots within almost any manufacturing or nonmanufacturing process. The book provides detailed coverage of the application of control charts, while also exploring critical topics such as regression, design of experiments, and Taguchi methods. In this new edition, the author continues to explain how to combine the many statistical methods explored in the book in order to optimize quality control and improvement. The book has been thoroughly revised and updated to reflect the latest research and practices in statistical methods and quality control, and new features include: Updated coverage of control charts, with newly added tools The latest research on the monitoring of linear profiles and other types of profiles Sections on generalized likelihood ratio charts and the effects of parameter estimation on the properties of CUSUM and EWMA procedures New discussions on design of experiments that include conditional effects and fraction of design space plots New material on Lean Six Sigma and Six Sigma programs and training Incorporating the latest software applications, the author has added coverage on how to use Minitab(r) software to obtain probability limits for attribute charts. new exercises have been added throughout the book, allowing readers to put the latest statistical methods into practice. Updated references are also provided, shedding light on the current literature and providing resources for further study of the topic. Statistical Methods for Quality Improvement, Third Edition is an excellent book for courses on quality control and design of experiments at the upper-undergraduate and graduate levels. the book also serves as a valuable reference for practicing statisticians, engineers, and physical scientists interested in statistical quality improvement"-- |c Provided by publisher | ||
| 520 | |a "In this new edition, the author continues to explain how to combine the many statistical methods explored in the book in order to optimize quality control and improvement. The book has been thoroughly revised and updated to reflect the latest research and practices in statistical methods and quality control, and new features include: Updated coverage of control charts, with newly added tools. The latest research on the monitoring of linear profiles and other types of profiles Sections on generalized likelihood ratio charts and the effects of parameter estimation on the properties of CUSUM and EWMA procedures"-- |c Provided by publisher | ||
| 504 | |a Includes bibliographical references and index. | ||
| 546 | |a English. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Quality control |x Statistical methods. | |
| 650 | 0 | |a Process control |x Statistical methods. | |
| 650 | 6 | |a Qualité |x Contrôle |x Méthodes statistiques. | |
| 650 | 7 | |a MATHEMATICS |x Probability & Statistics |x General. |2 bisacsh | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x Quality Control. |2 bisacsh | |
| 650 | 7 | |a TECHNOLOGY & ENGINEERING |x Quality Control. |2 bisacsh | |
| 650 | 7 | |a Process control |x Statistical methods |2 fast | |
| 650 | 7 | |a Quality control |x Statistical methods |2 fast | |
| 776 | 0 | 8 | |i Print version: |a Ryan, Thomas P., 1945- |t Statistical methods for quality improvement. |b 3rd ed. |d Hoboken, N.J. : Wiley, 2011 |z 9780470590744 |w (DLC) 2011022715 |w (OCoLC)728656846 |
| 830 | 0 | |a Wiley series in probability and statistics. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9780470590744/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 880 | 0 | 0 | |6 505-01/(S |g Contents note continued: |g 9.9. |t Effects of Parameter Estimation on ARLs -- |g 9.10. |t Dimension-Reduction and Variable Selection Techniques -- |g 9.11. |t Multivariate CUSUM Charts -- |g 9.12. |t Multivariate EWMA Charts -- |g 9.12.1. |t Design of a MEWMA Chart -- |g 9.12.2. |t Searching for Assignable Causes -- |g 9.12.3. |t Unequal Sample Sizes -- |g 9.12.4. |t Self-Starting MEWMA Chart -- |g 9.12.5. |t Combinations of MEWMA Charts and Multivariate Shewhart Charts -- |g 9.12.6. |t MEWMA Chart with Sequential Sampling -- |g 9.12.7. |t MEWMA Chart for Process Variability -- |g 9.13. |t Effect of Measurement Error -- |g 9.14. |t Applications of Multivariate Charts -- |g 9.15. |t Multivariate Process Capability indexes -- |g 9.16. |t Summary -- |t Appendix -- |t References -- |t Exercises -- |g 10. |t Miscellaneous Control Chart Topics -- |g 10.1. |t Pre-control -- |g 10.2. |t Short-Run SPC -- |g 10.3. |t Charts for Autocorrelated Data -- |g 10.3.1. |t Autocorrelated Attribute Data -- |g 10.4. |t Charts for Batch Processes -- |g 10.5. |t Charts for Multiple-Stream Processes -- |g 10.6. |t Nonparametric Control Charts -- |g 10.7. |t Bayesian Control Chart Methods -- |g 10.8. |t Control Charts for Variance Components -- |g 10.9. |t Control Charts for Highly Censored Data -- |g 10.10. |t Neural Networks -- |g 10.11. |t Economic Design of Control Charts -- |g 10.11.1. |t Economic-Statistical Design -- |g 10.12. |t Charts with Variable Sample Size and/or Variable Sampling Interval -- |g 10.13. |t Users of Control Charts -- |g 10.13.1. |t Control Chart Nonmanufacturing Applications -- |g 10.13.1.1. |t Healthcare -- |g 10.13.1.2. |t Financial -- |g 10.13.1.3. |t Environmental -- |g 10.13.1.4. |t Clinical Laboratories -- |g 10.13.1.5. |t Analytical Laboratories -- |g 10.13.1.6. |t Civil Engineering -- |g 10.13.1.7. |t Education -- |g 10.13.1.8. |t Law Enforcement/Investigative Work -- |g 10.13.1.9. |t Lumber -- |g 10.13.1.10. |t Forest Operations -- |g 10.13.1.11. |t Athletic Performance -- |g 10.13.1.12. |t Animal Production Systems -- |g 10.14. |t Software for Control Charting -- |t Bibliography -- |t Exercises -- |g pt. III |t BEYOND CONTROL CHARTS: GRAPHICAL AND STATISTICAL METHODS -- |g 11. |t Graphical Methods -- |g 11.1. |t Histogram -- |g 11.2. |t Stem-and-Leaf Display -- |g 11.3. |t Dot Diagrams -- |g 11.3.1. |t Digidot Plot -- |g 11.4. |t Boxplot -- |g 11.5. |t Normal Probability Plot -- |g 11.6. |t Plotting Three Variables -- |g 11.7. |t Displaying More Than Three Variables -- |g 11.8. |t Plots to Aid in Transforming Data -- |g 11.9. |t Summary -- |t References -- |t Exercises -- |g 12. |t Linear Regression -- |g 12.1. |t Simple Linear Regression -- |g 12.2. |t Worth of the Prediction Equation -- |g 12.3. |t Assumptions -- |g 12.4. |t Checking Assumptions Through Residual Plots -- |g 12.5. |t Confidence Intervals and Hypothesis Test -- |g 12.6. |t Prediction Interval for Y -- |g 12.7. |t Regression Control Chart -- |g 12.8. |t Cause-Selecting Control Charts -- |g 12.9. |t Linear, Nonlinear, and Nonparametric Profiles -- |g 12.10. |t Inverse Regression -- |g 12.11. |t Multiple Linear Regression -- |g 12.12. |t Issues in Multiple Regression -- |g 12.12.1. |t Variable Selection -- |g 12.12.2. |t Extrapolation -- |g 12.12.3. |t Multicollinear Data -- |g 12.12.4. |t Residual Plots -- |g 12.12.5. |t Regression Diagnostics -- |g 12.12.6. |t Transformations -- |g 12.13. |t Software For Regression -- |g 12.14. |t Summary -- |t References -- |t Exercises -- |g 13. |t Design of Experiments -- |g 13.1. |t Simple Example of Experimental Design Principles -- |g 13.2. |t Principles of Experimental Design -- |g 13.3. |t Statistical Concepts in Experimental Design -- |g 13.4. |t t-Tests -- |g 13.4.1. |t Exact t-Test -- |g 13.4.2. |t Approximate t-Test -- |g 13.4.3. |t Confidence Intervals for Differences -- |g 13.5. |t Analysis of Variance for One Factor -- |g 13.5.1. |t ANOVA for a Single Factor with More Than Two Levels -- |g 13.5.2. |t Multiple Comparison Procedures -- |g 13.5.3. |t Sample Size Determination -- |g 13.5.4. |t Additional Terms and Concepts in One-Factor ANOVA -- |g 13.6. |t Regression Analysis of Data from Designed Experiments -- |g 13.7. |t ANOVA for Two Factors -- |g 13.7.1. |t ANOVA with Two Factors: Factorial Designs -- |g 13.7.1.1. |t Conditional Effects -- |g 13.7.2. |t Effect Estimates -- |g 13.7.3. |t ANOVA Table for Unreplicated Two-Factor Design -- |g 13.7.4. |t Yates's Algorithm -- |g 13.8. |t 23 Design -- |g 13.9. |t Assessment of Effects Without a Residual Term -- |g 13.10. |t Residual Plot -- |g 13.11. |t Separate Analyses Using Design Units and Uncoded Units -- |g 13.12. |t Two-Level Designs with More Than Three Factors -- |g 13.13. |t Three-Level Factorial Designs -- |g 13.14. |t Mixed Factorials -- |g 13.15. |t Fractional Factorials -- |g 13.15.1. |t 2k-1 Designs -- |g 13.15.2. |t 2k-2 Designs -- |g 13.15.3. |t More Highly Fractionated Two-Level Designs -- |g 13.15.4. |t Fractions of Three-Level Factorials -- |g 13.15.5. |t Incomplete Mixed Factorials -- |g 13.15.6. |t Cautions -- |g 13.16. |t Other Topics in Experimental Design and Their Applications -- |g 13.16.1. |t Hard-to-Change Factors -- |g 13.16.2. |t Split-Lot Designs -- |g 13.16.3. |t Mixture Designs -- |g 13.16.4. |t Response Surface Designs -- |g 13.16.5. |t Designs for Measurement System Evaluation -- |g 13.16.6. |t Fraction of Design Space Plots -- |g 13.16.7. |t Computer-Aided Design and Expert Systems -- |g 13.16.8. |t Sequential Experimentation -- |g 13.16.9. |t Supersaturated Designs and Analyses -- |g 13.16.10. |t Multiple Responses -- |g 13.17. |t Summary -- |t References -- |t Exercises -- |g 14. |t Contributions of Genichi Taguchi and Alternative Approaches -- |g 14.1. |t "Taguchi Methods" -- |g 14.2. |t Quality Engineering -- |g 14.3. |t Loss Functions -- |g 14.4. |t Distribution Not Centered at the Target -- |g 14.5. |t Loss Functions and Specification Limits -- |g 14.6. |t Asymmetric Loss Functions -- |g 14.7. |t Signal-to-Noise Ratios and Alternatives -- |g 14.8. |t Experimental Designs for Stage One -- |g 14.9. |t Taguchi Methods of Design -- |g 14.9.1. |t Inner Arrays and Outer Arrays -- |g 14.9.2. |t Orthogonal Arrays as Fractional Factorials -- |g 14.9.3. |t Other Orthogonal Arrays Versus Fractional Factorials -- |g 14.9.4. |t Product Arrays Versus Combined Arrays -- |g 14.9.5. |t Application of Product Array -- |g 14.9.5.1. |t Cautions -- |g 14.9.6. |t Desirable Robust Designs and Analyses -- |g 14.9.6.1. |t Designs -- |g 14.9.6.2. |t Analyses -- |g 14.9.6.3. |t Experiment to Compare Product Array and Combined Array -- |g 14.10. |t Determining Optimum Conditions -- |g 14.11. |t Summary -- |t References -- |t Exercises -- |g 15. |t Evolutionary Operation -- |g 15.1. |t EVOP Illustrations -- |g 15.2. |t Three Variables -- |g 15.3. |t Simplex EVOP -- |g 15.4. |t Other EVOP Procedures -- |g 15.5. |t Miscellaneous Uses of EVOP -- |g 15.6. |t Summary -- |t Appendix -- |g 15.A. |t Derivation of Formula for Estimating σ -- |t References -- |t Exercises -- |g 16. |t Analysis of Means -- |g 16.1. |t ANOM for One-Way Classifications -- |g 16.2. |t ANOM for Attribute Data -- |g 16.2.1. |t Proportions -- |g 16.2.2. |t Count Data -- |g 16.3. |t ANOM When Standards Are Given -- |g 16.3.1. |t Nonconforming Units -- |g 16.3.2. |t Nonconformities -- |g 16.3.3. |t Measurement Data -- |g 16.4. |t ANOM for Factorial Designs -- |g 16.4.1. |t Assumptions -- |g 16.4.2. |t Alternative Way of Displaying Interaction Effects -- |g 16.5. |t ANOM When at Least One Factor Has More Than Two Levels -- |g 16.5.1. |t Main Effects -- |g 16.5.2. |t Interaction Effects -- |g 16.6. |t Use of ANOM with Other Designs -- |g 16.7. |t Nonparametric ANOM -- |g 16.8. |t Summary -- |t Appendix -- |t References -- |t Exercises -- |g 17. |t Using Combinations of Quality Improvement Tools -- |g 17.1. |t Control Charts and Design of Experiments -- |g 17.2. |t Control Charts and Calibration Experiments -- |g 17.3. |t Six Sigma Programs -- |g 17.3.1. |t Components of a Six Sigma Program -- |g 17.3.2. |t Six Sigma Applications and Programs -- |g 17.3.3. |t Six Sigma Concept for Customer Satisfaction -- |g 17.3.4. |t Six Sigma Training -- |g 17.3.5. |t Lean Six Sigma -- |g 17.3.6. |t Related Programs/Other Companies -- |g 17.3.6.1. |t SEMATECH's Qual Plan -- |g 17.3.6.2. |t AlliedSignal's Operational Excellence Program -- |g 17.4. |t Statistical Process Control and Engineering Process Control -- |t References. |
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