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ARL performance of residual control charts for trend AR(1) process: A case study on peroxide values of stored vegetable oil

机译:趋势AR(1)过程的残留控制图的ARL性能:以储存的植物油的过氧化物值为例

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For the purpose of process control, quality assurance engineers in a vegetable oil factory wonder the performance of the Shewhart, CUSUM, and EWMA residual control charts for peroxide values that show both serial autocorrelation between adjacent observations (autocorrelation) and upward linear trend. To deal with autocorrelated process data, a primary method is to apply these charts to the uncorrelated residuals of an appropriate time series model fitted to the data. In the relevant literature, although performances of the residual charts have been widely studied for autocorrelated processes, there exists no study that shows how these charts’ performances change by the addition of a particular type of trend in the autocorrelated data. In the present paper, average run length performances of these charts are computed for peroxide data from two batches, for which trend stationary first order autoregressive (trend AR(1) for short) model is a representative model.
机译:出于过程控制的目的,植物油工厂的质量保证工程师想知道Shewhart,CUSUM和EWMA残余控制图的过氧化物值的性能,这些图既显示相邻观测值之间的序列自相关(自相关)又显示线性趋势。为了处理自相关的过程数据,一种主要方法是将这些图表应用于适合该数据的适当时间序列模型的不相关残差。在相关文献中,尽管已经对残差图的性能进行了自相关过程的广泛研究,但尚无研究表明这些图如何被自动关联。通过在自相关数据中添加特定类型的趋势来更改性能。在本文中,针对来自两个批次的过氧化物数据计算了这些图表的平均游程长度性能,其中趋势平稳的一阶自回归模型(简称趋势AR(1))是一个代表模型。

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