Research on digital twin model for milling parameter optimization of thin-walled parts

Combined with digital twin technology, data-driven intelligent parameter optimization can be achieved, which is of great significance for realizing the intelligent manufacturing of thin-walled components. This study conducts a digital twin model study on parameter optimization of thin-walled parts milling processes. Firstly, the system architecture is developed based on the digital twin five-dimensional paradigm, enabling the interaction of virtual and real information through effective system connections. A milling parameter optimization method is devised, considering the goals of energy efficiency and material removal rate, as well as the limits imposed by the chatter factor. The other digital twin models, such as the energy consumption model and chatter model, are constructed to achieve the optimization model. Ultimately, the digital twin system is created, and the construction and testing of the system for the milling process are accomplished. The experiment confirms the efficacy of each function of the system.