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

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...

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Veröffentlicht in:International journal of production research 2022-04, Vol.60 (7), p.2312-2330
Hauptverfasser: Liu, Jinfeng, Zhao, Peng, Jing, Xuwen, Cao, Xuwu, Sheng, Sushan, Zhou, Honggen, Liu, Xiaojun, Feng, Feng
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container_end_page 2330
container_issue 7
container_start_page 2312
container_title International journal of production research
container_volume 60
creator Liu, Jinfeng
Zhao, Peng
Jing, Xuwen
Cao, Xuwu
Sheng, Sushan
Zhou, Honggen
Liu, Xiaojun
Feng, Feng
description 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.
doi_str_mv 10.1080/00207543.2021.1887531
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source EBSCOhost Business Source Complete; Taylor & Francis Journals Complete
subjects Digital twin
Digital twins
dynamic evolution
Economic impact
Evolution
Machining
machining features
process knowledge
title Dynamic design method of digital twin process model driven by knowledge-evolution machining features
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