(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.

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.

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