Manufacturing Capability Service Modeling, Management and Evaluation for Matching Supply and Demand in Cloud Manufacturing

被引:5
作者
Lin, Ting Yu [1 ,2 ,3 ]
Xiao, Yingying [1 ,2 ,3 ]
Yang, Chen [4 ]
Liu, Xiaoliang [1 ,2 ,3 ]
Li, Bo Hu [1 ]
Guo, Liqin [1 ,2 ]
Xing, Chi [1 ,2 ,3 ]
机构
[1] Beijing Simulat Ctr, Beijing Complex Prod Adv Mfg Engn Res Ctr, Beijing, Peoples R China
[2] Beijing Inst Elect Syst Engn, State Key Lab Intelligent Mfg Syst Technol, Beijing, Peoples R China
[3] Beijing Simulat Ctr, Sci & Technol Space Syst Simulat Lab, Beijing, Peoples R China
[4] Univ Hong Kong, Dept Ind & Mfg Syst Engn, HKU ZIRI Lab Phys Internet, Hong Kong, Hong Kong, Peoples R China
来源
THEORY, METHODOLOGY, TOOLS AND APPLICATIONS FOR MODELING AND SIMULATION OF COMPLEX SYSTEMS, PT III | 2016年 / 645卷
关键词
Cloud manufacturing; Manufacturing capability; Supply and demand matching; Service modeling; Service management; Service evaluation;
D O I
10.1007/978-981-10-2669-0_5
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Currently, the manufacturing sector faces challenges brought by the global technological revolution and industrial revolution. Cloud manufacturing can be of great help to break the traditional pattern of static enterprise resource configuration through the on-demand provision and consumption of manufacturing capability (MCap), and thus optimize industrial chains and improve competitiveness. Comparing to the traditional e-commerce, matching supply and demand of MCap will require the consideration of complex conditions, such as static and dynamic attributes of MCap services, scalability of domain attributes of heterogeneous MCap services, and other characteristics (e.g., multiple stakeholders and multi-round competition) in the open and dynamic environment of social manufacturing. To address the above demand, we propose meta-models for MCap service description, an approach to the management of MCap services based on the data model "EAV" and the enterprise search platform "Solr", and an approach to the evaluation of MCap services based on the dynamic composition & screening. Finally, those methods have been implemented in a cloud manufacturing platform for an aerospace conglomerate, and the results show their effectiveness.
引用
收藏
页码:35 / 48
页数:14
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