Open AccessX̅ and R control charts based on marshall-olkin inverse log-logistic distribution for positive skewed data
Author(s) -
Olubisi L. Aako,
Johnson Ademola Adewara,
Kayode S. Adekeye,
E. B. Nkemnole
Publication year - 2020
Publication title -
african journal of pure and applied sciences
Language(s) - English
Resource type - Journals
ISSN - 2710-0758
DOI - 10.33886/ajpas.v1i1.167
Subject(s) - control chart , statistics , skewness , control limits , shewhart individuals control chart , \bar x and r chart , statistical process control , mathematics , x bar chart , ewma chart , normal distribution , interval (graph theory) , computer science , process (computing) , combinatorics , operating system
The fundamental assumption of variable control charts is that the data are normally distributed and spread randomly about the mean. Process data are not always normally distributed, hence there is need to set up appropriate control charts that gives accurate control limits to monitor processes that are skewed. In this study Shewhart-type control charts for monitoring positively skewed data that are assumed to be from Marshall-Olkin Inverse Loglogistic Distribution (MOILLD) was developed. Average Run Length (ARL) and Control Limits Interval (CLI) were adopted to assess the stability and performance of the MOILLD control chart. The results obtained were compared with Classical Shewhart (CS) and Skewness Correction (SC) control charts using the ARL and CLI. It was discovered that the control charts based on MOILLD performed better and are more stable compare to CS and SC control charts. It is therefore recommended that for positively skewed data, a Marshall-Olkin Inverse Loglogistic Distribution based control chart will be more appropriate.