Overview

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 customers. The book exposes the pitfalls of assuming normality for all processes, describes how to test the normality assumption, and illustrates when non-normal distributions are likely to apply. It demonstrates how to handle uncooperative real-world processes that do not follow textbook assumptions. The text explains how to set realistic control limits and calculate meaningful process capability indices for non-normal applications. The book also addresses multivariate systems, nested variation sources, and process performance indices for non-normal distributions. The book includes examples from Minitab(R), StatGraphics(R) Centurion, and MathCAD and covers how to use spreadsheets to give workers a visual signal when an out of control condition is present. The included user disk provides Visual Basic for Applications functions to make tasks such as distribution fitting and tests for goodness of fit as routine as possible. The book shows you how to set up meaningful control charts and report process performance indices that actually reflect the process' ability to deliver quality.

Full Product Details

Author:   William A. Levinson
Publisher:   Taylor & Francis Inc
Imprint:   CRC Press Inc
Dimensions:   Width: 15.60cm , Height: 2.50cm , Length: 23.40cm
Weight:   0.589kg
ISBN:  

9781439820001

ISBN 10:   1439820007
Pages:   272
Publication Date:   21 December 2010
Audience:   College/higher education ,  General/trade ,  Tertiary & Higher Education ,  General
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Introduction. What to Expect From This book. Chapter Overview. Traditional Control Charts. Statistical Hypothesis Testing. Control Chart Concepts. Theoretical and Empirical Control Charts. Nonnormal Distributions. Data Fitting and Verification. Control Chart Construction: Center Line, Control Limits, and Zone Tests. Process Capability Indices. Nested Normal Distributions. Calculation of the variance components. Tests for Goodness of Fit. Control Chart. Process capability indices. Confidence Intervals for Process Capability Indices. Confidence Intervals for Cp. Confidence Intervals for CPL and CPU. The Noncentral t Distribution. Confidence Intervals for Cpk. The Bivariate Noncentral t Distribution. Exact Confidence Intervals for the Gamma Distribution Cpk. Multivariate Normal Systems. T' Chart. Calculation of Nonconforming Fraction, and a Capability Index.

Reviews

<p> a useful addition to the library of any industrial statistician, process engineer, or quality engineer engaged in improving processes. It represents material that is not typically covered in conventional books on statistical process control. In particular, with its focus on nonnormal distributions, this text provides a measure of reality that many quality and manufacturing professionals have known for years that not all process distributions follow the normal distribution. In that respect, this book is a refreshing addition to the literature and I highly recommend it.<br> Dean Neubauer, Journal of Quality Technology, Vol. 43, No. 4, October 2011

Author Information

William A. Levinson is the owner of Levinson Productivity Systems in Wilkes-Barre, Pennsylvania.

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