MODIFICATION OF CLEMENTS’ METHOD FOR ASSESSING THE CAPABILITY OF A NON-NORMAL PROCESS WITH AN APPLICATION

Year 2019, Volume: 20 Issue: 4, 446 - 457, 30.12.2019

Burcu Aytaçoğlu , Cemil Giray Genç

https://doi.org/10.18038/estubtda.514207

Abstract

In many industries process capability
studies are conducted in order to determine the capability of the process to
produce acceptable products and it is one of the important activities of
statistical process control. In order to express the capability of a process,
process capability indices are frequently used. However, they are usually
computed under the assumption that the process data follow a normal
distribution. Normality assumption may be violated and the use of these
traditional capability indices may cause misleading interpretation about the
capability of the process. One of the most widely discussed methods to handle
non-normality is Clements’ method which was proposed in 1989. Clements’ method
uses the Pearson family of curves for calculating capability indices for any
shape of distribution. It requires the estimation of the mean, standard
deviation, skewness and kurtosis and makes use of the classical estimators of
skewness and kurtosis. In this study, we discussed the use of more robust
estimators of skewness and kurtosis in the calculation of process capability
index by Clements’ method. For this purpose, capability indices with the use of
these robust estimators are computed by simulation and the mean square errors
of them are reported. The comparison is done through simulating Weibull and
lognormal data with several different parameter values. Finally, a real life
application to oil pump manufacturing in automotive industry is presented.

Keywords

Process Capability Index, Non-normality, Statistical Process Control, Skewed Population, Robust Estimator

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