single head hydraulic tube bending machine bending technology and CNC tube bending machine technology can realize data storage and management according to database technology. The application of database is now available in all walks of life. According to the characteristics of the bending process of the bending machine, combined with computer technology and database technology, domestic and foreign scholars have studied the method of improving the quality control of the bending process of the bending machine and optimizing the process parameters. Among them, American scholars proposed the bending-unloading-re-bending method to measure the rebound data, established the rebound prediction model, compensated the rebound method, and optimized the process control by establishing the rebound history database. This new method has higher accuracy than the traditional trial and error method. It is proposed to systematically establish the overall simulation model of the geometric motion deformation debugging and interference test of the CNC tube bending machine and the complete mold library and conduit library. The system is driven by numerical control command and can directly read the program from the pipe bending machine database. The three-dimensional dynamic display of the digital tube bending machine bending technology and the numerical control tube bending machine, such as clamping, bending and rebounding, and the interference detection processing can be performed to realize the bending process of the digital tube bending machine including digital bending Auxiliary design of method selection, tool, mold design and process parameters, thus greatly reducing the occurrence of defects such as wrinkles and excessive thinness in the bending process of the bender. These studies have realized the quality control of a certain aspect of the pipe bending machine to a certain extent, and the digital pipe bending machine bending process requires the cooperation of multiple molds, which is a multi-factor coupling interaction process, the numerical control pipe bending machine bending pipe The data management of the process should not only comprehensively study the influence relationship between its various factors, but also combine the characteristics of the bending process of the CNC pipe bending machine to establish a database that can fully meet the production and research needs, and need to establish a complete database. The system manages the data, effectively uses the data and is easy for the user to use to quickly determine the optimized process parameters and improve the quality of the bender bend. The scholars of Northwestern Poly technical University have established a reasonable finite element model for the simulation of thin-walled pipe bending, wrinkling and spring back prediction, and developed a three-dimensional numerical simulation system for the thin-walled tube numerical control bending precision forming process. The research reveals the thin-walled tube bending forming. The influencing factors and influence mechanism of wrinkling, rebound and cross-section distortion have accumulated a large number of research results and experimental data, which provides an important basis for establishing a reasonable digital tube bending machine data management system and optimizing process parameters. Based on the requirements of actual production and the needs of numerical simulation research, we studied the data management system of digital pipe bending machine bending process, and studied the application of multi-language of object-oriented to realize the function of the development environment. The system uses a database access interface, and the background uses a database built in Qv. The system can realize the functions of querying, invoking, deleting and modifying the parameters of the digital pipe bending machine bending pipe technology and the numerical control pipe bending machine, and initially realize the knowledge reasoning and obtain the causes and countermeasures of the defects, which can be searched in the database through query. The resulting data determines the optimized process parameters.