Cloud manufacturing simulation platform is used to simulate the collaboration and evolution, which among the resources, services, tasks, participants in cloud manufacturing environment. As an important part of the platform of simulation, simulation data generation method can effectively support the simulation accuracy. Data in cloud manufacturing environment are not completely random, and are closely related to the actual environment and resource characteristics. The workload of traditional random generate method or artificial method is very heavy and cannot completely rebuild the simulation environment. In this paper, Using clustering method to extract characteristics from an actual environment, and then extend the characteristics to generate new simulation data. To build a similar environment to the real environment used in the simulation. The result is shown that compared with the method to generate random data. This method can generate the reference data similar environment, the simulation can reflect the real effect in the process.
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ASME 2017 12th International Manufacturing Science and Engineering Conference collocated with the JSME/ASME 2017 6th International Conference on Materials and Processing
June 4–8, 2017
Los Angeles, California, USA
Conference Sponsors:
- Manufacturing Engineering Division
ISBN:
978-0-7918-5074-9
PROCEEDINGS PAPER
Research on Data Generation Method in Cloud Manufacturing Simulation Platform
Chun Zhao
Beihang University, Beijing, China
Lin Zhang
Beihang University, Beijing, China
Paper No:
MSEC2017-2904, V003T04A041; 5 pages
Published Online:
July 24, 2017
Citation
Zhao, C, & Zhang, L. "Research on Data Generation Method in Cloud Manufacturing Simulation Platform." Proceedings of the ASME 2017 12th International Manufacturing Science and Engineering Conference collocated with the JSME/ASME 2017 6th International Conference on Materials and Processing. Volume 3: Manufacturing Equipment and Systems. Los Angeles, California, USA. June 4–8, 2017. V003T04A041. ASME. https://doi.org/10.1115/MSEC2017-2904
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