Journal Published Online: 31 August 2018
Volume 48, Issue 2

Run Sum Chart for the Mean with Auxiliary Information

CODEN: JTEVAB

Abstract

The use of the auxiliary information (AI) method in control charts is gaining increasing attention. Many studies have shown that auxiliary information-based charts can boost the charts’ performances in the detection of out-of-control signals. In this study, a run sum chart for the mean based on auxiliary characteristics (abbreviated as the RS-AI chart) is proposed. The optimization designs of the RS-AI chart in minimizing the steady-state out-of-control average run length (ARL) and expected average run length (EARL) are developed. The formulae to compute the steady-state ARL and EARL of the RS-AI chart are derived using the Markov chain approach. The RS-AI chart is compared with the Shewhart AI, synthetic AI, and exponentially weighted moving average AI charts. The results show that the RS-AI chart outperforms the competing charts for all shift sizes when the correlation between the auxiliary and the study variable is large. A numerical example is given to demonstrate the implementation of the RS-AI chart.

Author Information

Ng, Peh Sang
School of Mathematical Sciences, Universiti Sains Malaysia, Minden, Penang, Malaysia
Khoo, Michael Boon Chong
School of Mathematical Sciences, Universiti Sains Malaysia, Minden, Penang, Malaysia
Saha, Sajal
School of Mathematical Sciences, Universiti Sains Malaysia, Minden, Penang, Malaysia
Teh, Sin Yin
School of Management, Universiti Sains Malaysia, Minden, Penang, Malaysia
Pages: 22
Price: $25.00
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Details
Stock #: JTE20170707
ISSN: 0090-3973
DOI: 10.1520/JTE20170707