Abstract—The observations are not always identically and independently distributed (i.i.d.) in continuous manufacturing which most observations is skewed away normal distribution. In this research aim to study the performance of Tukey's control chart for detecting a change in parameter when observation are from skew distributions such as exponential and Laplace distributions. Also, the performance of Tukey’s control chart is compared with Shewhart and Exponentially Weighted Moving Average (EWMA) charts. The Average Run Length is commonly measured the performance of control chart. The ARL0 is usually used when the process is in-control (sufficient large) and the ARL1 is correctly signaled to be out- of-control (minimum). The Tukey's control chart is superior to other charts for large shift; however, the EWMA performs better for small to moderate shifts. The Tukey's control chart is very easy to setup the control limits and use a simple statistical concept.
Index Terms—Average Run Length, Skew Distributions, EWMA, Tukey's Control Chart, Robustness.