面向数字孪生的制造系统健康状态分析

Health State Analysis of Manufacturing System for Digital Twin

数字孪生体的建模和与物理实体间的交互都以数据映射的方式实现,为日益复杂的制造系统健康状态分析提供了新思路。针对产品质量、机床性能和任务执行状态,构建数据交互融合的数字孪生车间健康状态评估和预测框架;建立综合考虑设备性能退化和产品质量对故障率影响的机床故障期望函数,并提出了任务可靠性与产品质量相关联的Copula制造系统健康表达。以某柴油机缸盖制造系统为例,结果表明所提方法能动态高效地判断制造系统健康状态,有效识别不同因素对制造系统健康状态的影响。

The modeling of digital twin and the interaction with physical entity are realized by data mapping,which provides a new idea for the increasingly complex health state analysis of manufacturing system.Aiming at product quality,machine tool performance and task execution status,a framework for health status assessment and prediction of digital twin workshop based on data interaction and fusion is constructed;A machine tool failure expectation function is established,which comprehensively considers the effects of equipment performance degradation and product quality on the failure rate,and a copula manufacturing system health expression is proposed,in which task reliability is associated with product quality.Taking the manufacturing system of diesel engine cylinder head as an example,the results show that the proposed method can dynamically and efficiently judge the health state of the manufacturing system and effectively identify the influence of different factors on the health state of the manufacturing system.