Process Monitoring under a Sequential Sampling design

Control chart is a popular technique that is widely used in statistical process control to identify any possible deviations from a stable state of a process. Shewhart charts are famous for identifying larger shifts, while Cumulative-sum and exponentially weighted moving average (EWMA) control charts are well-known for identifying smaller shifts in process parameters. For data obtained sequentially, each additional data point may potentially provide a cause for a shift in the process. Thus, a careful monitoring of the process is needed within this setup. This study therefore examines the performance of sequential based control charts (such as the Shewhart and the EWMA sequential based charts) for observing the location of normally distributed process. The performance of these new control charts will be observed by using several overall Run Length properties (like Average, Median and Standard Deviation). The comparative study is expected to reveal that the overall performance of the proposed design is much better than existing counterparts for sequentially collected data. A real life data set from steel rod manufacturing industry will be considered to show the real life illustration of proposed design.