Abstract
In this paper, a new variable control chart is proposed using multiple dependent-state repetitive sampling by assuming that the data follows a normal distribution having a symmetry property. Its efficiency will be evaluated in terms of in-control and out-of-control average run lengths. The results showed that the proposed chart is better than the existing variable control chart to detect an early shift in the process. An industrial example is given to illustrate the proposed chart in the industry.
Highlights
Control charts are powerful, effective and important tools which are frequently used to detect unusual variation in the manufacturing process
upper control limit (UCL) and or the process may be considered out of control even if all points are within the control limits utilizing nine or more points in a row that are on the same side of the mean
Aslam et al [13] introduced multiple dependent state (MDS) sampling in the area of control charts, which utilizes the previous subgroup information if the decision cannot be made based on the first sample
Summary
Effective and important tools which are frequently used to detect unusual variation in the manufacturing process. The Shewhart [1] X-bar control chart is very common to detect a shift in the mean of the process [2]. The control charts using single sampling make a decision about the state of the process by plotting statistics computed from the single sample. The efficiency of control charts to detect a shift in the process can be improved using other sampling schemes [14]. Introduced the repetitive sampling in the area of the control chart which allows to repeat the sampling process if the plotting statistic lies in the in-decision state. Aslam et al [13] introduced multiple dependent state (MDS) sampling in the area of control charts, which utilizes the previous subgroup information if the decision cannot be made based on the first sample.
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