Department of Mathematics and Statistics, Riphah International University, Muzaffarabad, Pakistan.
Department of Statistics, University of Azad Jammu and Kashmir, Pakistan.
PLoS One. 2020 Feb 26;15(2):e0229422. doi: 10.1371/journal.pone.0229422. eCollection 2020.
Control charts are popular tools in the statistical process control toolkit and the exponentially weighted moving average (EWMA) chart is one of its essential component for efficient process monitoring. In the present study, a new Bayesian Modified-EWMA chart is proposed for the monitoring of the location parameter in a process. Four various loss functions and a conjugate prior distribution are used in this study. The average run length is used as a performance evaluation tool for the proposed chart and its counterparts. The results advocate that the proposed chart performs very well for the monitoring of small to moderate shifts in the process and beats the existing counterparts. The significance of the proposed scheme has proved through two real-life examples: (1) For the monitoring of the reaming process which is used in the mechanical industry. (2) For the monitoring of golf ball performance in the sports industry.
控制图是统计过程控制工具包中流行的工具，指数加权移动平均 (EWMA) 图是有效过程监控的基本组成部分之一。在本研究中，提出了一种新的贝叶斯改进 EWMA 图，用于监控过程中的位置参数。本研究使用了四种不同的损失函数和共轭先验分布。平均运行长度被用作提出的图表及其对应图表的性能评估工具。结果表明，该建议图表在监控过程中的小到中度偏移方面表现非常出色，优于现有对应图表。通过两个实际案例证明了该方案的重要性：（1）用于监控机械行业中使用的铰孔过程。（2）用于监控运动行业中高尔夫球的性能。
