孪生数据驱动的绿色切削工艺优选决策

为了快速优选低碳且具有环境友好性的绿色切削工艺，提出了一种孪生数据驱动的绿色工艺优选决策方法。首先，建立了数字孪生驱动的切削加工工艺优选决策流程；其次，以加工质量、加工时间、加工成本、资源消耗、环境影响为一级评价指标，建立了绿色切削工艺优选评价指标体系；再次，采用网络层次分析法对评价指标进行权重计算，并基于概率犹豫模糊理想值法及孪生数据对备选的绿色切削工艺进行优选决策；最后，以某航空企业的叶片加工工艺优选为例进行实例验证。结果表明：该方法能够充分利用数字孪生车间的仿真预测、历史数据挖掘、实时采集等功能，以孪生数据的形式为工艺评价提供全面的数据源；同时所建立的评价决策模型实用性较强，符合现实的切削工艺优选决策场景，模型求解方法鲁棒性好。

Digital Twin Data Driven Decision-making for Green Cutting Process

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, which included quality, time, cost, resource consumption and environmental impact as the evaluation indexes. Then 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.