Aluminum extrusion is considered as one of the very challenging processes to produce good quality and low cost products. This paper presents an optimization design of the X-bar&R chart for effective statistical monitoring of output of aluminum extrusion process. The proposed optimal X-bar&R chart is compared with traditional 3-σ X-bar&R chart, in terms of the average extra quadratic loss (AEQL), for detecting a wide range of shifts in the mean and variance. The results reveal that the optimal X-bar&R chart overtakes the 3-σ X-bar&R chart by 94%, in terms of AEQL. In addition, the former has the smallest out-of-control average time to signal (ATS) over almost all shifts. Consequently, the replacement of traditional X-bar&R chart by the optimal one is recommended to detect the mean and variance shifts more efficiently and as a result, reduce the process variation and avoid economic loss.