This article presents an optimization design of the Xbar&EWMA chart for monitoring a cold rolling process producing galvanized steel coils. Using real data from industry, the results show that the detection effectiveness of  the Xbar&EWMA charts is better than the optimal  chart and the optimal EWMA chart in terms of Expected Average Number of Observation required to identify an out-of-control case (EANOS) by about 36% and 10%, respectively. The optimization design of the Xbar&EWMA charts ensures that extra inspection resources will not be necessary, and the false alarm rate of the charts will not be increased.