An exponentially weighted moving average control chart based on signed ranks for finite horizon processes

IF 1.3 4区 工程技术 Q4 ENGINEERING, INDUSTRIAL
T. Perdikis, G. Celano, S. Psarakis, P. Castagliola
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引用次数: 0

Abstract

Abstract Distribution-free control charts are an efficient quality monitoring tool to inspect lots of parts manufactured within a finite production horizon. In this work, the performance of the Exponentially Weighted Moving Average chart based on the Wilcoxon signed rank statistic is investigated for on-line monitoring of finite production runs. The chart’s on-target performance is evaluated through a specific non-homogeneous Markov chain model under different process scenarios. A numerical analysis is conducted for determining its optimal design and a performance comparison with other available schemes is presented for different symmetric distributions of observations. Finally, an illustrative example is presented to show a practical implementation of the investigated chart.
有限水平过程的指数加权移动平均控制图
无分布控制图是一种有效的质量监控工具,可以对有限生产周期内生产的大量零件进行检验。在这项工作中,基于Wilcoxon符号秩统计的指数加权移动平均图的性能研究用于有限生产运行的在线监测。通过特定的非齐次马尔可夫链模型,在不同的工艺场景下对图表的目标性能进行评估。通过数值分析确定了该方案的最优设计,并对不同对称分布的观测值与其他方案进行了性能比较。最后,给出了一个示例来展示所研究图表的实际实现。
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来源期刊
Quality Engineering
Quality Engineering ENGINEERING, INDUSTRIAL-STATISTICS & PROBABILITY
CiteScore
3.90
自引率
10.00%
发文量
52
审稿时长
>12 weeks
期刊介绍: Quality Engineering aims to promote a rich exchange among the quality engineering community by publishing papers that describe new engineering methods ready for immediate industrial application or examples of techniques uniquely employed. You are invited to submit manuscripts and application experiences that explore: Experimental engineering design and analysis Measurement system analysis in engineering Engineering process modelling Product and process optimization in engineering Quality control and process monitoring in engineering Engineering regression Reliability in engineering Response surface methodology in engineering Robust engineering parameter design Six Sigma method enhancement in engineering Statistical engineering Engineering test and evaluation techniques.
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