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- W1990321336 abstract "Abstract It has been repeatedly demonstrated that X-bar quality control charts perform poorly when the process subgroups being monitored are correlated. In this paper, we propose and investigate the performance of a control chart that accounts for subgroup correlations in a general Gaussian process. The time-series innovations algorithm is used to construct the desired chart from a set of one-step ahead predictions and prediction variances. The chart is applicable in both stationary and nonstationary settings. A simulation study shows that this ‘innovations’ chart performs as a traditional X-bar chart even when the correlation structure of the process must be estimated from a small number of subgroups. The innovations chart is then used to study a data set of motor shaft diameters which has correlated subgroups. The results here show that erroneous conclusions can be reached if subgroup correlations are ignored." @default.
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- W1990321336 date "1998-07-01" @default.
- W1990321336 modified "2023-09-27" @default.
- W1990321336 title "A control chart for a general Gaussian process" @default.
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- W1990321336 doi "https://doi.org/10.1016/s0378-3758(97)00180-8" @default.
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