Median and interquartile range control charts based on quantiles of Marshall-Olkin inverse log-logistic distribution Online publication date: Thu, 01-Feb-2024
by Olubisi L. Aako; Johnson A. Adewara; Kayode S. Adekeye
International Journal of Industrial and Systems Engineering (IJISE), Vol. 46, No. 2, 2024
Abstract: The presence of outliers makes process data deviate from normality and reduces the sensitivity of control charting procedures. This paper proposed a robust method of determining the control limits of X̄ and R charts in the presence of outliers when the data deviates from normality. The quantile of Marshall-Olkin inverse log-logistic distribution (MOILLD) is derived. The quantiles of the distribution are then used to estimate the process location and dispersion for the construction of control limits of median and interquartile range control charts. Control limit interval, false alarm rate, and average run length were used to compare the performance of the proposed control charts with similar control charts in the literature. The results showed that the proposed method detects out-of-control faster than the classical Shewhart control chart and robust control charts whose control limits were based on raw data.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Industrial and Systems Engineering (IJISE):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook