On Designing Semi Parametric & Non-Parametric Control Charts For Process Monitoring

Statistical process control (SPC) tools are employed to handle an industrial production process by maintaining products qualities. Control charts are one of the most famous tools of SPC which maintain process stability by detecting disturbances, also known as special causes. Disturbances known as shifts in process which appear due to the faults in a process. The shifts are normally categorized as small, medium, and large amount in SPC language. To handle large shifts, we generally implement Shewhart control charts. For small to moderate shifts, we apply cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts. For practical considerations, we need to design flexible charts that might be used when distribution of a variable of interest is unknown and/or limited number of samples is possible for producing the control limits. The same is the motivation of this study. We intend to design some new semi-parametric and non-parametric control charts under traditional and ranked set sampling schemes. The real applications will be presented to support the study.