A variable sample size side-sensitive synthetic coefficient of variation chart

IF 1.7 4区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS
Sok Li Lim, W. C. Yeong, Z. L. Chong, Chew Peng Gan, M. Khoo
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引用次数: 0

Abstract

A major challenge for control charts monitoring the coefficient of variation is to quickly detect shifts in this parameter, so that assignable cause(s) can be quickly removed and the process can operate in an in-control state with a stable coefficient of variation. This is especially so when there are constraints in the sample size. One proposed strategy is to vary the sample size according to the most recent information. However, a side-sensitive synthetic chart monitoring the coefficient of variation with variable sample size is not available. This paper contributes to the literature by developing a variable sample size side-sensitive synthetic chart for the coefficient of variation. The main contributions are in terms of illustrating the operations of the chart, deriving the formulae to evaluate its performance and developing the algorithms to optimize its performance. Comparisons with current charts show that the proposed chart outperforms all existing synthetic-type charts monitoring the coefficient of variation. The proposed chart also outperforms the variable sample size coefficient of variation chart for all shift sizes. In addition, it outperforms the variable sample size run sum and variable sample size Exponentially Weighted Moving Average charts monitoring the coefficient of variation for moderate and large shift sizes.
可变样本量侧敏合成变异系数图
监控变异系数的控制图所面临的一个主要挑战是如何快速检测出该参数的变化,从而快速消除可归因的原因,并使流程在变异系数稳定的控制状态下运行。当样本量受到限制时,尤其如此。一种建议的策略是根据最新信息改变样本量。然而,目前还没有一个侧敏合成图来监测样本量可变时的变异系数。本文通过为变异系数绘制可变样本量侧敏合成图,为相关文献做出了贡献。本文的主要贡献在于说明了图表的操作,推导出评估其性能的公式,并开发了优化其性能的算法。与现有图表的比较表明,建议的图表优于所有现有的变异系数合成图表。在所有移位大小的情况下,建议的图表也优于可变样本大小的变异系数图表。此外,在监测中等和较大移位规模的变异系数方面,它优于可变样本量运行总和图表和可变样本量指数加权移动平均图表。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.10
自引率
16.70%
发文量
203
审稿时长
3.4 months
期刊介绍: Transactions of the Institute of Measurement and Control is a fully peer-reviewed international journal. The journal covers all areas of applications in instrumentation and control. Its scope encompasses cutting-edge research and development, education and industrial applications.
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