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SPC with correlated observations for the chemical and process industries
Author(s) -
Mastrangelo Christina M.,
Montgomery Douglas C.
Publication year - 1995
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.4680110203
Subject(s) - control chart , statistical process control , autocorrelation , ewma chart , uncorrelated , control limits , shewhart individuals control chart , chart , computer science , statistics , process (computing) , statistical hypothesis testing , moving average , data mining , mathematics , operating system
In the use of statistical control charts, violating the basic assumption of independent or uncorrelated data results in a chart that exhibits poor statistical performance, resulting in an increased number of false alarms. Autocorrelated data requires modifications to traditional control chart techniques. A method based on the exponentially weighted moving average that uses variable control limits is presented. Using simulation, we explore the shift detection properties of this moving centre‐line technique and will show how the detection capability of the procedure can be enhanced using supplemental tracking signal tests. Guidelines and conditions for use are also presented.