共查询到20条相似文献,搜索用时 15 毫秒
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Gulab Singh Bura 《统计学通讯:理论与方法》2019,48(14):3439-3450
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Mohammad Hossein Poursaeed 《统计学通讯:理论与方法》2020,49(7):1761-1767
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Mehdi Katebi 《Journal of Statistical Computation and Simulation》2019,89(15):2813-2830
An economic statistical model of the exponentially weighted moving average (EWMA) control chart for the average number of nonconformities in the sample is proposed. The statistical and economic performance of proposed design are evaluated using the average run length (ARL) and the hourly expected cost, respectively. A Markov chain approach is applied to derive expressions for ARL. The cost model is established based on the general cost function given in Lorenzen and Vance [The economic design of control charts: a unified approach. Technometrics. 1986;28:3–11]. An example is provided to illustrate the application of the proposed model. A sensitivity analysis is also carried out to investigate the effects of model parameters on the solution of the economic statistical design by using the design of experiments (DOE) technique. 相似文献
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Zailei Cheng 《统计学通讯:理论与方法》2013,42(23):5850-5861
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The Shewhart-type control chart is traditionally developed under the normality assumption. In practice, however, this assumption may not hold. Because the skew normal distribution represents a broad distribution class and is more flexible than is the normal distribution, we propose two new control charts to monitor process mean and spread for skew normal distributed data. Moreover, to facilitate practical implementation, tables of charting constants are provided. We conducted simulation studies to compare the false alarm rates, and the results show that new proposed charts perform better than others as skewness increases. Finally, an illustrative example is provided. 相似文献
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M. A. A. Cox 《统计学通讯:理论与方法》2013,42(20):5050-5057
AbstractThe adoption of control charts can be traced to the classic text by Shewhart (1931) and championed by many writers since then, including Deming (1982). Numerous other texts and publications stress the continuing importance of this area. While tables of key Shewhart control chart parameters are extremely useful they are easily lost or mislaid and can sometimes be difficult to interpret. To address this issue spreadsheet code is implemented to produce all the key control chart factors. 相似文献
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