孪生数据驱动的绿色切削工艺优选决策.

In order to quickly select the low carbon and environment friendly green cutting process, a digital twin data driven decision- making method for green process was proposed. Firstly, digital twin data driven decision-making process for green cutting process was determined. Secondly, the evaluation index system of green cutting process optimization was established, including quality, time, cost, resource consumption and environmental impact as the evaluation indexes. Thirdly, the network analytic hierarchy was used to calculate the weight of the evaluation attributes. The probabilistic hesitant fuzzy reference ideal method and digital twin data was used to select the alternative green cutting process. Finally, the evaluation model was applied to the blade processing optimization of an aviation enterprise. The results show that the proposed method can make full use of the functions of digital twin workshop including simulation prediction, historical data mining and real-time acquisition, which provide a comprehensive data source for process evaluation. At the same time, the proposed evaluation model is practical, robust and suitable for the green cutting process evaluation. [ABSTRACT FROM AUTHOR]