Statistical methods for quality improvement

Statistical methods for quality improvement / Thomas P. Ryan.

Praise for the Second Edition ""As a comprehensive statistics reference book for quality improvement, it certainly is one of the best books available.""--Technometrics This new edition continues to provide the most current, proven statistical methods for quality control and quali...

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Bibliographic Details
Main Author: Ryan, Thomas P., 1945-
Format: eBook
Language:English
Published: Oxford : Wiley-Blackwell, 2011.
Edition:3rd ed.
Subjects:
Quality control > Statistical methods.
MATHEMATICS > Probability & Statistics > General.
Quality control > Statistical methods
Kvalitetskontroll.
Online Access:Click for online access
Table of Contents:
  • Statistical Methods forQuality Improvement; Contents; Preface; Preface to the Second Edition; Preface to the First Edition; PART I FUNDAMENTAL QUALITY IMPROVEMENT AND STATISTICAL CONCEPTS; 1 Introduction; 1.1 Quality and Productivity; 1.2 Quality Costs (or Does It?); 1.3 The Need for Statistical Methods; 1.4 Early Use of Statistical Methods for Improving Quality; 1.5 Influential Quality Experts; 1.6 Summary; References; 2 Basic Tools for Improving Quality; 2.1 Histogram; 2.2 Pareto Charts; 2.3 Scatter Plots; 2.3.1 Variations of Scatter Plots; 2.4 Control Chart; 2.5 Check Sheet.
  • 2.6 Cause-and-Effect Diagram2.7 Defect Concentration Diagram; 2.8 The Seven Newer Tools; 2.8.1 Affinity Diagram; 2.8.2 Interrelationship Digraph; 2.8.3 Tree Diagram; 2.8.4 Prioritization Matrix; 2.8.5 Matrix Diagram; 2.8.6 Process Decision Program Chart; 2.8.7 Activity Network Diagram; 2.9 Software; 2.10 Summary; References; Exercises; 3 Basic Concepts in Statistics and Probability; 3.1 Probability; 3.2 Sample Versus Population; 3.3 Location; 3.4 Variation; 3.5 Discrete Distributions; 3.5.1 Binomial Distribution; 3.5.2 Beta-Binomial Distribution; 3.5.3 Poisson Distribution.
  • 3.5.4 Geometric Distribution3.5.5 Negative Binomial Distribution; 3.5.6 Hypergeometric Distribution; 3.6 Continuous Distributions; 3.6.1 Normal Distribution; 3.6.2 t Distribution; 3.6.3 Exponential Distribution; 3.6.4 Lognormal Distribution; 3.6.5 Weibull Distribution; 3.6.6 Extreme Value Distribution; 3.6.7 Gamma Distribution; 3.6.8 Chi-Square Distribution; 3.6.9 Truncated Normal Distribution; 3.6.10 Bivariate and Multivariate Normal Distributions; 3.6.11 F Distribution; 3.6.12 Beta Distribution; 3.6.13 Uniform Distribution; 3.7 Choice of Statistical Distribution; 3.8 Statistical Inference.
  • 3.8.1 Central Limit Theorem3.8.2 Point Estimation; 3.8.2.1 Maximum Likelihood Estimation; 3.8.3 Confidence Intervals; 3.8.4 Tolerance Intervals; 3.8.5 Hypothesis Tests; 3.8.5.1 Probability Plots; 3.8.5.2 Likelihood Ratio Tests; 3.8.6 Bonferroni Intervals; 3.9 Enumerative Studies Versus Analytic Studies; References; Exercises; PARTII CONTROL CHARTS AND PROCESS CAPABILITY; 4 Control Charts for Measurements With Subgrouping (for One Variable); 4.1 Basic Control Chart Principles; 4.2 Real-Time Control Charting Versus Analysis of Past Data.
  • 4.3 Control Charts: When to Use, Where to Use, How Many to Use4.4 Benefits from the Use of Control Charts; 4.5 Rational Subgroups; 4.6 Basic Statistical Aspects of Control Charts; 4.7 Illustrative Example; 4.7.1 R-Chart; 4.7.2 R-Chart with Probability Limits; 4.7.3 S-Chart; 4.7.4 S-Chart with Probability Limits; 4.7.5 S2-Chart; 4.7.6 X-Chart; 4.7.7 Recomputing Control Limits; 4.7.8 Applying Control Limits to Future Production; 4.7.9 Combining an X- and an S-Chart; 4.7.10 Standards for Control Charts; 4.7.11 Deleting Points; 4.7.12 Target Values; 4.8 Illustrative Example with Real Data.

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