TY  - JOUR
T1  - A Robust Cumulative Sum Control Chart for Monitoring the Process
Mean based on a High Breakdown Point Scale Estimator
AU - Rahman, Ayu Abdul AU - Yahaya, Sharipah Soaad Syed AU - Atta, Abdu Mohammed Ali 
JO  - Journal of Engineering and Applied Sciences
VL  - 13
IS  - 10
SP  - 3423
EP  - 3429
PY  - 2018
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2018.3423.3429
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2018.3423.3429
KW  - Average Run Length (ARL)
KW  -Standard Deviation of the Run Length (SDRL)
KW  -percentile of the run length
KW  -contaminated normal distribution
KW  -CUSUM control chart
KW  -MADn
AB  - Unlike traditional Shewhart Chart, Cumulative Sum (CUSUM) chart is more sensitive to small and
moderate shifts. Nonetheless, its reliability in monitoring the mean shifts is usually hampered by the underlying
distribution of the data. Although, apparent cause of non-normality is owed to outliers, their presence may
simply be a genuine part of the process rather than attributing to the special causes. To set these occasional
outliers apart from the real distributional shifts, numerous extensions of the CUSUM charts have been
suggested. One possible way is via robust estimation. This paper proposes a simple, yet effective way to make
the chart highly effective for detecting small sustained shifts. A very robust scale estimator, namely Median
Absolute Deviation about the median (MADn) is used as an estimate for dispersion. The performance
evaluation of the proposed chart for monitoring mean shift is compared with the standard CUSUM chart using
several aspects of the run length distribution the Average Run Length (ARL), Standard Deviation of the Run
Length (SDRL) and percentile run length. The simulation results indicate the robust CUSUM chart efficiency
in detecting small magnitude of shifts in both normal and outlier-prone data.
ER  -