Adaptive Modification of Digital Twin Model of CNC Machine Tools Coordinately Driven by Mechanism Model and Data Model

Abstract

Abstract The digital twin of CNC machine tools has become one of the important technical means to realize intelligent manufacturing. To reflect the real conditions of the whole life cycle of the machine tools, an adaptive modification method of the digital twin model of CNC machine tools coordinately driven by mechanism model and data model is proposed. Taking the dynamic stiffness of the CNC machine tool as the combined object, firstly the finite element method is used to establish the initial digital twin mechanism model, then the simulation data of the mechanism model is used to generate enough samples to establish a surrogate model to realize the construction of the initial data model. At different stages of the life cycle of CNC machine tools, the minimum deviation between the dynamic response obtained by the simulation of the digital twin model and the measured response is set as the objective function, and intelligent optimization algorithm is adopted to adaptively modify the digital twin model to ensure the consistency between the digital twin model and the physical object. The established digital twin model is used to predict the dynamic performance of CNC machine tools, which lays the foundation for the whole life cycle management decision of CNC machine tools.