Additive Manufacturing Cloud via Peer-Robot Collaboration
When building a 3D printing cloud manufacturing platform, self-sensing and collaboration on manufacturing resources present challenging problems. This paper proposes a peer-robot collaboration framework to deal with these issues. Each robot combines heterogeneous additive manufacturing hardware and...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2016-05-01
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| Series: | International Journal of Advanced Robotic Systems |
| Online Access: | https://doi.org/10.5772/63938 |
| _version_ | 1818500677210472448 |
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| author | Yuan Yao Dong Chen Lei Wang Xiaoming Yang |
| author_facet | Yuan Yao Dong Chen Lei Wang Xiaoming Yang |
| author_sort | Yuan Yao |
| collection | DOAJ |
| description | When building a 3D printing cloud manufacturing platform, self-sensing and collaboration on manufacturing resources present challenging problems. This paper proposes a peer-robot collaboration framework to deal with these issues. Each robot combines heterogeneous additive manufacturing hardware and software, acting as an intelligent agent. Through collaboration with other robots, it forms a dynamic and scalable integration manufacturing system. The entire distributed system is managed by rules that employ an internal rule engine, which supports rule conversion and conflict resolution. Two additive manufacturing service scenarios are designed to analyse the efficiency and scalability of the framework. Experiments show that the presented method performs well in tasks requiring large-scale access to resources and collaboration. |
| first_indexed | 2024-12-10T20:45:57Z |
| format | Article |
| id | doaj.art-1b24d76634d548529c7dc315ff6fceb2 |
| institution | Directory Open Access Journal |
| issn | 1729-8814 |
| language | English |
| last_indexed | 2024-12-10T20:45:57Z |
| publishDate | 2016-05-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | International Journal of Advanced Robotic Systems |
| spelling | doaj.art-1b24d76634d548529c7dc315ff6fceb22022-12-22T01:34:14ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142016-05-011310.5772/6393810.5772_63938Additive Manufacturing Cloud via Peer-Robot CollaborationYuan Yao0Dong Chen1Lei Wang2Xiaoming Yang3 Shanghai Key Laboratory of Manufacturing Automation and Robotics, Shanghai, China Rapid Manufacture Engineering Center, Shanghai University, Shanghai, China Rapid Manufacture Engineering Center, Shanghai University, Shanghai, China School of Computer Science, Huzhou University, Zhejiang Huzhou, ChinaWhen building a 3D printing cloud manufacturing platform, self-sensing and collaboration on manufacturing resources present challenging problems. This paper proposes a peer-robot collaboration framework to deal with these issues. Each robot combines heterogeneous additive manufacturing hardware and software, acting as an intelligent agent. Through collaboration with other robots, it forms a dynamic and scalable integration manufacturing system. The entire distributed system is managed by rules that employ an internal rule engine, which supports rule conversion and conflict resolution. Two additive manufacturing service scenarios are designed to analyse the efficiency and scalability of the framework. Experiments show that the presented method performs well in tasks requiring large-scale access to resources and collaboration.https://doi.org/10.5772/63938 |
| spellingShingle | Yuan Yao Dong Chen Lei Wang Xiaoming Yang Additive Manufacturing Cloud via Peer-Robot Collaboration International Journal of Advanced Robotic Systems |
| title | Additive Manufacturing Cloud via Peer-Robot Collaboration |
| title_full | Additive Manufacturing Cloud via Peer-Robot Collaboration |
| title_fullStr | Additive Manufacturing Cloud via Peer-Robot Collaboration |
| title_full_unstemmed | Additive Manufacturing Cloud via Peer-Robot Collaboration |
| title_short | Additive Manufacturing Cloud via Peer-Robot Collaboration |
| title_sort | additive manufacturing cloud via peer robot collaboration |
| url | https://doi.org/10.5772/63938 |
| work_keys_str_mv | AT yuanyao additivemanufacturingcloudviapeerrobotcollaboration AT dongchen additivemanufacturingcloudviapeerrobotcollaboration AT leiwang additivemanufacturingcloudviapeerrobotcollaboration AT xiaomingyang additivemanufacturingcloudviapeerrobotcollaboration |