TY - JOUR
T1 - Hypernetwork-based manufacturing service scheduling for distributed and collaborative manufacturing operations towards smart manufacturing
AU - Cheng, Ying
AU - Bi, Luning
AU - Tao, Fei
AU - Ji, Ping
N1 - Publisher Copyright:
© 2018, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2020/10/1
Y1 - 2020/10/1
N2 - In the future smart manufacturing, both of sensor-based environment in shop floors and cloud-based environment among more and more enterprises are deployed gradually. Various distributed and separated manufacturing facilities are as collaborative cloud services, integrated and aggregated with their real-time information. It provides opportunities for the distributed and collaborative manufacturing operations across lots of distributed but networked enterprises on demand with enough flexibility. To this end, the scheduling problem and its result of those collaborative services for distributed manufacturing operations play an important role in improving manufacturing utilization and efficiency. In this paper, we put forward the hypernetwork-based models introducing the thought of graph coloring and an artificial bee colony algorithm based method for this scheduling problem. Three groups of experiments are carried out respectively to discuss therein different situations of distributed and collaborative manufacturing operations, i.e., in a private cloud, in a public cloud, and in a hybrid cloud. Some future studies with further consideration of collaboration equilibrium, dynamic control and data-based intelligence, are finally pointed out in the conclusion.
AB - In the future smart manufacturing, both of sensor-based environment in shop floors and cloud-based environment among more and more enterprises are deployed gradually. Various distributed and separated manufacturing facilities are as collaborative cloud services, integrated and aggregated with their real-time information. It provides opportunities for the distributed and collaborative manufacturing operations across lots of distributed but networked enterprises on demand with enough flexibility. To this end, the scheduling problem and its result of those collaborative services for distributed manufacturing operations play an important role in improving manufacturing utilization and efficiency. In this paper, we put forward the hypernetwork-based models introducing the thought of graph coloring and an artificial bee colony algorithm based method for this scheduling problem. Three groups of experiments are carried out respectively to discuss therein different situations of distributed and collaborative manufacturing operations, i.e., in a private cloud, in a public cloud, and in a hybrid cloud. Some future studies with further consideration of collaboration equilibrium, dynamic control and data-based intelligence, are finally pointed out in the conclusion.
KW - Complex networks
KW - Distributed collaboration
KW - Graph coloring
KW - Manufacturing service scheduling
KW - Smart manufacturing (SM)
UR - https://www.scopus.com/pages/publications/85044441060
U2 - 10.1007/s10845-018-1417-8
DO - 10.1007/s10845-018-1417-8
M3 - 文章
AN - SCOPUS:85044441060
SN - 0956-5515
VL - 31
SP - 1707
EP - 1720
JO - Journal of Intelligent Manufacturing
JF - Journal of Intelligent Manufacturing
IS - 7
ER -