Comparison of control charts for autocorrelated process control Online publication date: Thu, 21-Jan-2010
by Canan Bilen, Xianzhe Chen
International Journal of Quality Engineering and Technology (IJQET), Vol. 1, No. 2, 2009
Abstract: Conventional control charts were developed for industrial processes in which successive observations were assumed to be independent and identically distributed; an assumption often violated in practice. Approaches to monitoring autocorrelated data range from using conventional control charts, with adjusted control limits, to using Hotelling T² statistics on a moving window of observations from the univariate autocorrelated process of interest. Although there are many different approaches to monitoring autocorrelated processes, there are no guidelines on choosing the procedure with the best average run length performance for a particular level of autocorrelation and shift magnitude of interest. This paper presents a guideline for choosing proper control charts for various conditions based on average run length performance. A Monte Carlo simulation study is designed to provide a comparative evaluation of the average run length performance of autocorrelated process control charts.
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