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On mixed memory control charts based on auxiliary information for efficient process monitoring
Quality and Reliability Engineering International ( IF 2.3 ) Pub Date : 2020-06-24 , DOI: 10.1002/qre.2667
Syed Masroor Anwar 1, 2 , Muhammad Aslam 2 , Muhammad Riaz 3 , Babar Zaman 4
Affiliation  

Control charts are popular monitoring tools in statistical process control toolkit. These are used to identify assignable causes in the process parameters (location and/or dispersion). These assignable causes result in a shift in the process parameter(s). The shift can be categorized into three sizes (small, moderate, and large). Memory control charts such as the exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) charts are effective for identifying small‐to‐moderate shift(s) in the process. Likewise, mixed memory control charts are useful for efficient process monitoring. In this study, we have proposed two new mixed memory control charts based on auxiliary information named MxMEC and MxMCE control charts to improve the efficiency of these mixed charts. The MxMEC chart is a merger of the auxiliary information based MxEWMA chart and the classical CUSUM chart. Likewise, the MxMCE chart integrates the auxiliary information based MxCUSUM with the classical EWMA chart. The proposed MxMEC and MxMCE charts are evaluated through famous performance measures including average run length, extra quadratic loss, relative average run length, and performance comparison index. The performance of the study proposals is compared with the existing counterparts such as the classical CUSUM and EWMA, MxCUSUM, MxEWMA, MEC, MCE, and runs rules‐based CUSUM charts. The comparisons revealed the superiority of the proposed charts against other competing charts particularly for small‐to‐moderate shifts in the process location. Finally, a real‐life data is used to show the implementation procedure of the proposed charts in practical situations.

中文翻译:

基于辅助信息的混合内存控制图可进行有效的过程监控

控制图是统计过程控制工具包中流行的监视工具。这些用于识别过程参数(位置和/或分散)中的可分配原因。这些可分配原因导致过程参数发生偏移。班次可以分为三种大小(小,中和大)。内存控制图(例如指数加权移动平均值(EWMA)和累积和(CUSUM)图)可有效地识别过程中的中小偏移。同样,混合内存控制图对于有效的过程监控很有用。在这项研究中,我们基于辅助信息提出了两个新的混合内存控制图,分别称为MxMEC和MxMCE控制图,以提高这些混合图的效率。MxMEC图表是基于辅助信息的MxEWMA图表和经典CUSUM图表的合并。同样,MxMCE图表将基于辅助信息的MxCUSUM与经典EWMA图表集成在一起。拟议的MxMEC和MxMCE图表通过著名的性能指标进行评估,包括平均游程长度,额外二次损失,相对平均游程长度和性能比较指数。将研究建议书的表现与经典CUSUM和EWMA,MxCUSUM,MxEWMA,MEC,MCE等现有对等物进行比较,并运行基于规则的CUSUM图表。比较显示了拟议图表相对于其他竞争图表的优越性,特别是对于过程位置的小到中度变动。最后,
更新日期:2020-06-24
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