@inproceedings{d0574d624adb409ba14b37c6495f3898,
title = "Digital Twin-Enabled Production Optimization for Steel Industry",
abstract = "Pressures from the market and environment have put forward higher demands to the steel industry, which drive the need to achieve a deeper integration between physical production factory and cyber information system. In this study, a digital twin (DT) platform for hot-rolling production is built based on the whole-process data acquisition, data-driven process modeling, multi-flow coupling modeling and integrated planning and optimization technologies. Surrounding the DT platform, the integrated planning and production scheduling framework for the medium plate plant is introduced. The slab design problem of medium plates is analyzed in detail and solved by Python with an actual production dataset. The developed DT platform has been implemented in a large steel plant, and experimental results show the effectiveness of the proposed model.",
keywords = "Digital twin, slab design, steel production",
author = "Gongzhuang Peng and Yinliang Cheng and Xuejun Zhang and Dong Xu and Shenglong Jiang",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 25th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2022 ; Conference date: 04-05-2022 Through 06-05-2022",
year = "2022",
doi = "10.1109/CSCWD54268.2022.9776025",
language = "英语",
series = "2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1126--1131",
booktitle = "2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2022",
address = "美国",
}