A New Sum of Squares Exponentially Weighted Moving Average Control Chart Using Auxiliary Information

Symmetry

卷:12

Shin-Li Lu¹  Jen-Hsiang Chen² 

[1] Department of Industrial Management and Enterprise Information, Aletheia University, 32 Chen-Li Street, Tamsui, New Taipei City 251, Taiwan;

[2] Department of Information Management, Shih Chien University Kaohsiung Campus, 200 University Road, Neimen Dist, Kaohsiung City 84550, Taiwan;

关键词: auxiliary information;    average run length;    SSEWMA chart;    statistical process control;   

DOI  :  10.3390/sym12111888

来源: DOAJ

【 摘 要 】

The concept of control charts is based on mathematics and statistics to process forecast; which applications are widely used in industrial management. The sum of squares exponentially weighted moving average (SSEWMA) chart is a well-known tool for effectively monitoring both the increase and decrease in the process mean and/or variability. In this paper, we propose a novel SSEWMA chart using auxiliary information, called the AIB-SSEWMA chart, for jointly monitoring the process mean and/or variability. With our proposed chart, the attempt is to enhance the performance of the classical SSEWMA chart. Numerical simulation studies indicate that the AIB-SSEWMA chart has better detection ability than the existing SSEWMA and its competitive maximum EWMA based on auxiliary information (AIB-MaxEWMA) charts in view of average run lengths (ARLs). An illustrated example is used to demonstrate the efficiency of the proposed AIB-SSEWMA chart in detecting small process shifts.

【 授权许可】

Unknown