Statistical Methods for Quality ImprovementA comprehensive, up-to-date survey of statistical methods for quality improvement Statistical methods for quality improvement offer numerous benefits for industry and business, both through identifying existing trouble spots and alerting management and technical personnel to potential problems. In the Second Edition of his successful book that is still unrivaled in content, Tom Ryan continues to offer clear, thorough coverage of all available techniques-from basic control charts to regression and design of experiments, and the combined use of these tools. This edition is fully expanded and revised, bringing readers up to date with very recent research and providing a solid foundation from which to explore the statistical literature. Dr. Ryan tackles complicated topics in a logical, engaging, easy-to-understand style, downplaying mathematical formulas and making the material accessible to industrial engineers and applied statisticians alike. Special features of Statistical Methods for Quality Improvement, Second Edition include: Greatly expanded chapters on process capability indices and multivariate control chart methods Improved attributes control charts based on the author's research A detailed presentation of Six Sigma programs A new, separate chapter on CUSUM and EWMA procedures New material on robust design and Taguchi-type procedures Chapter appendices for more in-depth coverage of selected topics Very extensive and up-to-date references in each chapter, in addition to a bibliography of papers on a variety of control chart applications |
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Common terms and phrases
3-sigma limits analysis ANOM ANOVA applied approach approximately assignable cause Assume assumption binomial distribution Chapter computed confidence interval considered constructed control charts control limits correlation CUSUM procedure CUSUM scheme data in Table decision lines degrees of freedom denotes detecting determine discussed estimate EVOP EWMA example experiment factors Figure fractional factorial illustrated in-control ARL individual observations Journal of Quality levels loss function main effects mean shift Minitab moving range multivariate chart nonconforming units nonnormality normal distribution np chart number of nonconforming obtained parameter Pareto chart Poisson Poisson distribution problem process capability indices process control process mean process variables Quality Control quality improvement Quality Technology random variable regression residuals sample Section Shewhart significant Six Sigma specification limits standard deviation statistical process control subgroup averages Taguchi target value Technometrics transformation treatment combinations two-factor interactions univariate variance Woodall zero