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Self‐adapting control charts
Author(s) -
Albers Willem,
Kallenberg Wilbert C. M.
Publication year - 2006
Publication title -
statistica neerlandica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 39
eISSN - 1467-9574
pISSN - 0039-0402
DOI - 10.1111/j.1467-9574.2006.00330.x
Subject(s) - control chart , nonparametric statistics , normality , statistics , computer science , variance (accounting) , statistical process control , parametric statistics , control (management) , shewhart individuals control chart , control limits , mathematics , ewma chart , artificial intelligence , process (computing) , accounting , business , operating system
When the distributional form of the observations differs from normality, standard control charts are often prone to serious errors. Such model errors can be avoided by using (modified) nonparametric control charts. Unfortunately, these control charts suffer from large stochastic errors caused by estimation. In between these two types are the so‐called parametric control charts. All three of them, as well as a combined chart, which chooses one of the three control charts according to the appropriate model assumption on the underlying distribution are discussed in this paper. The data indicate which of the three control charts to select. Readymade formulas for the several control charts are presented accompanied by an application on real data. Apart from bias removal, criteria based on exceedance probability and semi‐variance are investigated.