Dynamic design method of digital twin process model driven by knowledge-evolution machining features

被引:38
作者
Liu, Jinfeng [1 ]
Zhao, Peng [1 ]
Jing, Xuwen [1 ]
Cao, Xuwu [1 ]
Sheng, Sushan [1 ]
Zhou, Honggen [1 ]
Liu, Xiaojun [2 ]
Feng, Feng [3 ]
机构
[1] Jiangsu Univ Sci & Technol, Sch Mech Engn, Zhenjiang 212003, Jiangsu, Peoples R China
[2] Southeast Univ, Sch Mech Engn, Nanjing, Peoples R China
[3] Shaanxi Diesel Engine Heavy Ind Co Ltd, Xingping, Peoples R China
基金
中国国家自然科学基金;
关键词
Digital twin; process knowledge; machining features; dynamic evolution;
D O I
10.1080/00207543.2021.1887531
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Machining plan is the core of guiding manufacturing production and is regarded as one of the keys to ensure the quality of product processing. Existing process design methods are inefficient to quickly handle the machining plan changed induced by the unpredictable events in real-time production. It inevitably causes time and economic losses for the enterprise. In order to express the evolutionary characteristics of product processing, the construction method of digital twin process model (DTPM) is proposed based on the knowledge-evolution machining features. Three key technologies include correlation structure of process knowledge, expression method of the evolution geometric features and the association mechanism between two are solved. On this basis, the construction framework of DTPM is illustrated. Then, the organisation and management mechanism of multi-source heterogeneous data is discussed in detail. At last, a case study of the complex machined part is researched, the results show that the processing time reduced by about 7% and the processing stability improved by 40%. Meanwhile, the implementation scheme, application process and effect of this case are described in detail to provide reference for enterprises.
引用
收藏
页码:2312 / 2330
页数:19
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