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Performance of Tukey's and Individual/Moving Range Control Charts
Author(s) -
Khaliq QuratUlAin,
Riaz Muhammad,
Alemi Farrokh
Publication year - 2015
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.1664
Subject(s) - statistics , control chart , log normal distribution , standard deviation , mathematics , range (aeronautics) , weibull distribution , poisson distribution , moving average , computer science , engineering , process (computing) , aerospace engineering , operating system
This paper compares two control charts: Tukey (TCC) and individual/moving range (XmR) control charts. Both are designed to examine single observation per time period, but little is known about which one is more efficient and under what conditions. We simulated data from different distributions and examined the performance of the two control charts on these data. Performance was assessed using the of average run length, extra quadratic loss, median run length, standard deviation run length, performance comparison index, and relative average run length. Overall, TCC was more efficient than XmR, when observations had binomial, Rayleigh, logistic, lognormal, Maxwell, normal, Poisson, Weibull (with α = 10, β = 1), and Student's t (30 and 10 degrees of freedom) distributions. XmR was more efficient when observations had Student's t (with 4 degrees of freedom) and gamma (with α = 4, β = 1) distributions. These results suggest that improvement teams could reach faster conclusions if they use TCC in most common situations. Copyright © 2014 John Wiley & Sons, Ltd.