Abstract: In order to recognize the abnormal pattern of control chart to enhance the automation level of quality management and promote E-management of manufacturing enterprise,in this paper the quality data generated by Monte Carlo simulation is coded through lionear transformation to improve the character of the patterns,and then the two kinds of neural networks are applied to recognize the control chart patterns.Through analyzing the test result,the application strategy of control chart recognition is proposed.