Job Shop Scheduling Based on Digital Twin Technology: A Survey and an Intelligent Platform
Author(s) -
Haifei Yu,
Songjian Han,
Dongsheng Yang,
Zhiyong Wang,
Wei Feng
Publication year - 2021
Publication title -
complexity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 61
eISSN - 1099-0526
pISSN - 1076-2787
DOI - 10.1155/2021/8823273
Subject(s) - scheduling (production processes) , computer science , cloud computing , big data , industrial engineering , job shop scheduling , industry 4.0 , digital manufacturing , flow shop scheduling , field (mathematics) , job shop , manufacturing engineering , distributed computing , engineering , data mining , operations management , embedded system , routing (electronic design automation) , operating system , mathematics , pure mathematics
The concept of digital twinning has become a hot topic in the manufacturing industry in recent years. The emerging digital twin technology is an intelligent technology that makes full use of multimodels, big data, and interdisciplinary knowledge, which provides some new approaches for the field of the intelligent manufacturing industry. The job shop scheduling problem has been an important research field in the discrete manufacturing industry. Digital twin technology is adopted to solve the problem of job shop scheduling, which provides the possibility for the intelligent development of workshops. Based on digital twin technology and combined with the actual problem of production line scheduling, we propose a new intelligent scheduling platform to solve the shop scheduling problems above. Meanwhile, based on the prediction and diagnosis of multisource dynamic interference in the workshop production process by big data analysis technology, the corresponding interference strategy is formulated in advance by the scheduling cloud platform. The model simulation experiment of intelligent dispatching cloud platform was carried out, and some enterprises in intelligent manufacturing workshop were taken as examples to verify the superiority of the dispatching cloud platform. Finally, we look forward to the future research direction of intelligent manufacturing based on digital twin technology.
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