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Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/135133

Title:	Loss-based control charts for monitoring non-normal process data
Authors:	楊素芬 Yang, Su-Fen Shen, Lijuan
Contributors:	統計系
Keywords:	Control charts;Process control;Gaussian distribution;Standards;Monitoring;Probability density function;Loss measurement
Date:	2020-04
Issue Date:	2021-05-25 14:12:54 (UTC+8)
Abstract:	Quality and loss of products are crucial factors in competitive companies, and firms widely adopt a loss function to measure the loss caused by a deviation in the quality variable from the target value. From Taguchi`s view point, it is important to monitor any deviation from the process target value. While most existing studies assume the quality variable follows a normal distribution, the distribution can in fact be skewed or deviate from normal in practice. This paper thus proposes loss-based control charts for monitoring the quality loss location or equivalently the deviation of the quality variable from the target value under a skew-normal distribution. We consider the exponentially weighted moving average (EWMA) average loss control chart, which illustrates the best performance in detecting an out-of-control loss location for a process with a left-skewed distribution. Numerical analysis demonstrates that the proposed EWMA average loss chart always performs better than the existing median loss chart for both left-skewed and right-skewed distributions. A numerical example illustrates the application of the proposed EWMA average loss control chart.
Relation:	IEEE ACCESS, Vol.8, No.1, pp.91163-91169
Data Type:	article
DOI link:	https://doi.org/10.1109/ACCESS.2020.2989400
DOI:	10.1109/ACCESS.2020.2989400
Appears in Collections:	[Department of International Business] Periodical Articles

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