NDLI: Univariate Nonparametric Process Control

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Univariate Nonparametric Process Control

Content Provider	Scilit
Author	Qiu, Peihua
Copyright Year	2013
Description	The SPC control charts discussed in the previous several chapters, for monitoring univariate or multivariate continuous numerical quality characteristics, are all based on the assumption that the related quality characteristics follow normal distributions when the production process in question is IC and after it becomes OC. As pointed out in Subsection 2.3.1, normal distributions play an important role in statistics, be- cause many continuous numerical variables in practice roughly follow normal dis- tributions and much statistical theory is developed for normally distributed random variables. An intuitive explanation about the reason many continuous numerical vari- ables in our daily life roughly follow normal distributions can be given using the central limit theorem (CLT) discussed in Subsection 2.7.1. For instance, a quality characteristic in question (e.g., the lifetime of a machine) is often affected by many different factors, including the quality of the raw material, labor, manufacturing fa- cilities, proper operation in the manufacturing process, and so forth (cf., Figure 1.1 in Section 1.2). So, by the CLT, its distribution would be roughly normal. Book Name: Introduction to Statistical Process Control
Related Links	https://content.taylorfrancis.com/books/download?dac=C2010-0-33543-1&isbn=9780429090776&doi=10.1201/b15016-12&format=pdf
Ending Page	401
Page Count	48
Starting Page	354
DOI	10.1201/b15016-12
Language	English
Publisher	Informa UK Limited
Publisher Date	2013-10-14
Access Restriction	Open
Subject Keyword	Book Name: Introduction To Statistical Process Control Manufacturing Engineering Manufacturing Quality Characteristics Statistical Normal Distributions Roughly Continuous Numerical Follow Normal
Content Type	Text
Resource Type	Chapter

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