Hybrid Double Exponentially Weighted Moving Average (HDEWMA) Control Chart ForInverse Rayleigh Distribution
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Date
2021-12-15
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UMT.Lahore
Abstract
The Control charts are the most important tool of Statistical Process Control (SPC) tool kit.
The “assignable and un-assignable causes” are differentiated via control charts. The
objective of the potent process monitoring system is to identify the presence of an
“assignable cause”. In this thesis, we have proposed a Hybrid Double Exponentially
Weighted Moving Average HDEWMA control chart. The proposed control chart is based on
Inverse Rayleigh Distributed lifetimes using simple random sampling (SRS) and ranked set
sampling (RSS). Out-of-control-Average Run Length (ARL1) is used to evaluate the
performance of the proposed control chart. The HDEWMA control chart is compared with
traditional/simple EWMA and CUSUM control charts. The performance of the control chart
is evaluated using out of control average run length (ARL1). A real-life example is used to
compare the proposed HDEWMA, traditional/simple EWMA chart and CUSUM control
chart. It is observed that the proposed HDEWMA control chart outperforms simple EWMA
and CUSUM control charts. The HDEWMA control chart can be used for efficient
monitoring of the production process in manufacturing industries where the data is coming
from inverse Rayleigh Distribution.