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CRC Press
Published: Tuesday, January 11, 2011 - 11:22
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 indexes for non-normal applications. The book also addresses multivariate systems, nested variation sources, and process performance indexes for non-normal distributions.
The book includes examples from Minitab, StatGraphics 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 indexes that actually reflect the process’ ability to deliver quality.
Features include:
• Explains pitfalls in assuming normality for all processes
Author William A. Levinson is the owner of Levinson Productivity Systems in Wilkes-Barre, Pennsylvania.
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How to explain non-normal applications to suppliers and customers
(CRC Press: Boca Raton, FL) -- Traditional statistical process control assumes that manufacturing process data come from a normal bell-curve distribution. Numerous supplier reports and in-house control charts are essentially meaningless, because their creators do not know how to check the normality assumption or what to do if they recognize a non-normal application. Statistical Process Control for Real-World Applications by William A. Levinson (CRC Press, 2010) shows how to handle uncooperative, real-world processes that do not follow textbook assumptions.
• Explores instances in which the lognormal, gamma, and Weibull distributions might occur in real-world processes
• Illustrates how to deal with nested variation sources that are common in batch manufacturing operations
• Discusses what process capability indexes are, how they relate to Six Sigma, and how to calculate them for non-normal applications
• Shows how to handle multivariate systems
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