TY - JOUR
T1 - A data- And knowledge-driven framework for digital twin manufacturing cell
AU - Zhang, Chao
AU - Zhou, Guanghui
AU - He, Jun
AU - Li, Zhi
AU - Cheng, Wei
N1 - Publisher Copyright:
© 2019 The Authors. Published by Elsevier B.V.
PY - 2019
Y1 - 2019
N2 - Intelligent manufacturing is regarded as the next generation manufacturing mode with powerful learning and cognitive capacities enabled by new generation information technologies such as Internet of Things, big data analytics, edge computing and artificial intelligence. To provide an insight into intelligent manufacturing, this paper takes autonomous manufacturing cell as implementation scenario and proposes a data- and knowledge-driven framework for digital twin manufacturing cell (DTMC), which could support autonomous manufacturing by an intelligent perceiving, simulating, understanding, predicting, optimizing and controlling strategy. In addition, three key enabling technologies including digital twin model, dynamic knowledge bases and knowledge-based intelligent skills for supporting the above strategy are analyzed. Then, the implementing methods of DTMC are introduced through a thus constructed digital twin robot, and the usage of data and knowledge for supporting the automous operations of DTMC is also discussed. Finally, benefits of DTMC in smart product-service systems (PSS) and its current challenges are summarized.
AB - Intelligent manufacturing is regarded as the next generation manufacturing mode with powerful learning and cognitive capacities enabled by new generation information technologies such as Internet of Things, big data analytics, edge computing and artificial intelligence. To provide an insight into intelligent manufacturing, this paper takes autonomous manufacturing cell as implementation scenario and proposes a data- and knowledge-driven framework for digital twin manufacturing cell (DTMC), which could support autonomous manufacturing by an intelligent perceiving, simulating, understanding, predicting, optimizing and controlling strategy. In addition, three key enabling technologies including digital twin model, dynamic knowledge bases and knowledge-based intelligent skills for supporting the above strategy are analyzed. Then, the implementing methods of DTMC are introduced through a thus constructed digital twin robot, and the usage of data and knowledge for supporting the automous operations of DTMC is also discussed. Finally, benefits of DTMC in smart product-service systems (PSS) and its current challenges are summarized.
KW - Digital twin
KW - Digital twin manufacturing cell
KW - Intelligent manufacturing
KW - Smart product-service systems
UR - https://www.scopus.com/pages/publications/85070560451
U2 - 10.1016/j.procir.2019.04.084
DO - 10.1016/j.procir.2019.04.084
M3 - 会议文章
AN - SCOPUS:85070560451
SN - 2212-8271
VL - 83
SP - 345
EP - 350
JO - Procedia CIRP
JF - Procedia CIRP
T2 - 11th CIRP Conference on Industrial Product-Service Systems, CIRP IPS2 2019
Y2 - 29 May 2019 through 31 May 2019
ER -