Statistical control charts are widely used in industry for process and measurement control . in this paper we study the use of markov chain approach in calculating the average run length (ARL) of cumulative sum (Cusum) control chart for defect the shifts in the mean of process , and exponentially weighted moving average (EWMA) control charts for defect the shifts for process mean and , the standard deviation . Also ,we used the EWMA charts based on the logarithm of the sample variance for monitoring a process standard deviation when the observations (products are selected from al_mamun factory ) are identically and independently distributed (iid) from normal distribution in continuous manufacturing . The case study approach used as the appropriate approach to reach the research objectives , all of the (Product toothpaste Anber , Product Hand Cream Balsam , Product Menem Eutur fabrics, and Bathroom Cleaner Rwnaq ) represent for the research sample , the statistical methods used are the Cusum and EWMA chats And the adoption of the (ARL) and (SDRL) obtained using  the method of Markov chain.

The researcher recommended that the application of the standard Average Run length of ARL to reach the production process and disciplined statistically reduce deviations in the production process for the target value .