基于DEVS的机械加工过程碳排放多粒度动态模型构建及仿真

Multi-granularity Dynamic Model Establishment and Simulation of Carbon Emissions for Machining Process Based on DEVS

机械加工过程碳排放分析是低碳制造(Low carbon manufacturing, LCM)技术发展、创新及应用的基础。针对加工过程中的离散性、动态性及加工设备的高度非线性特点,同时为充分反映多设备、多工艺特征下的各类外部、内部事件对加工过程碳排放的影响,提出一种基于离散事件系统规范(Discrete event system specification,DEVS)的机械加工过程碳排放多粒度动态模型与仿真方法。基于对加工过程层级结构及碳排放特性的分析,采用DEVS分层阶梯建模方法,并结合信息控制下的加工运行机制及调度规则,构建设备层、工作组层、工艺链层的碳排放多粒度动态模型。以某全数控磨床尾架主轴的加工过程为例,基于Eclipse平台下的CD++Builder插件设计了各层次DEVS仿真模型,并通过所开发的仿真应用程序,对模型及方法进行了验证。该方法对于构建规范化、形式化的加工过程碳排放模型,实现加工过程各层级碳排放的实时动态分析与预测、定量评估低碳加工单元具有较广阔的应用前景。

The carbon emissions analysis on machining process is the base of the development, innovation and application on Low Carbon Manufacturing(LCM) technology. According to the characteristic of discreteness and dynamism during manufacturing, as well as the highly nonlinear features on processing equipment, meanwhile, for the purpose of fully reflect the carbon emissions variation when various external and internal events occurs under the multiple equipment and processes circumstances. A method for multi-granularity dynamic model establishment and simulation of carbon emissions on machining process based on Discrete Event System Specification(DEVS) is proposed. Based on comprehensive analysis of the hierarchical structure and carbon emissions characteristic of machining process, multi-granularity carbon emissions analysis models on process chain level, workstation level, and machine level are established by employing the hierarchical modeling structure of DEVS associate with the running mechanism and scheduling rules. The model is applied to a tailstock spindle machining process. The DEVS simulation models on each level are designed by using CD++Builder plug-in based on Eclipse. The corresponding simulation program is developed to verify the effectiveness of proposed method. The results show that the method is suitable to establish the standardized and formalized carbon emissions model of machining process. And the model can provide real-time dynamic analysis and prediction of carbon emissions during manufacturing, and quantitative evaluate low carbon processing unit, which has significance in practice.