Firstly, under known conditions, the dynamic scheduling model of RGV intelligent vehicle is established by analyzing the process under different processing conditions. Through this model, the optimal route and the shortest time for RGV intelligent vehicle to respond to CNC of NC machine tool in material processing are obtained. At the same time, RGV scheduling strategy and system operation efficiency are given. For the material processing operation of a process, each CNC is equipped with the same cutting tool, and the material can be processed on any CNC. According to the Dijstra algorithm in the shortest path and the first-come-first-service scheduling algorithm, the first case can be simulated and analyzed. The optimal route and the shortest time between RGV and each CNC can be obtained. According to the two algorithms, the dynamic scheduling model in this case can be reflected by C++ programming, and then the qualitative analysis can be made to obtain the results of processing data of a process in one shift at this time. For the material processing operation of two processes, the first and second processes of each material are processed by two different CNCs in turn. According to hypothesis validation, in the case of two working procedures, eight CNCs are allocated reasonably to two different cutting tools in different order to find out the optimal allocation method, and through this allocation method, the same algorithm is adopted as in the first case, and then the qualitative analysis is made to obtain the data results of the two working procedures in one shift at this time. For the case that CNC may fail in the process of processing, we can reduce the number of faults according to the rescheduling strategy and the job shop scheduling algorithm, simplify the complexity, and then combine the results of the previous processing with the two models established before in two different situations to get two sets of different data.