Construction and application of digital twin model for tool wear monitoring and life prediction

Abstract

Aiming at the problems existing in accurate monitoring of tool wear status and accurate prediction of tool life, there is no reliable basis for decision-making on tool selection, replacement and grinding, which seriously affects the optimization and control of precise tool utilization and the dynamic regulation of production systems. Aiming at this problem, based on the concept of digital twin, a digital twin model for tool wear monitoring and life prediction is proposed. The model consists of three parts: digital model, analysis data model and evaluation model. Complete the collection and fusion of heterogeneous data and the evaluation and prediction for different targets. According to the different wear stages of the tool, three monitoring and prediction modes are proposed. Make full use of the value of multi-dimensional data information. Monitoring and forecasting services are provided for different demand levels, taking the cost, efficiency and accuracy of forecasting. into account, Supports the precise use of tools.