Optimal Design of Intelligent Manufacturing Execution System Based on Artificial Intelligence and Decision Tree Algorithm

The traditional manufacturing system is a pyramid hierarchical structure, and its planning, scheduling and control are centralized and serial, which lacks flexibility and cannot adapt to the frequent adjustment of production organization mode and the dynamic change of product demand under the condition of global market competition. Aiming at the development trend of intelligent MES (manufacturing execution system), this paper introduces AI (artificial intelligence) and DT (decision tree) algorithms into intelligent MES, and establishes an intelligent MES optimization model based on AI and DT algorithms. An improved GA (genetic algorithm) based on LSTM (Long short-term memory) with improved fitness function is proposed to solve the production scheduling problem. Using C4.5 algorithm based on normal distribution, the construction time of classifier is effectively shortened. The experimental results show that the fitness value of the improved GA is 10.93% higher than that of the standard GA, which proves the optimization effect of the improved GA algorithm on the fitness function. The experimental results show that this method meets the basic requirements of intelligent MES. It can monitor enterprises in all directions and visually, and realize integrated enterprise management and control.