Development of Auto-scaling Cloud Manufacturing Framework for machine tool industry

Chao Chun Chen, Yu Chuan Lin, Min Hsiung Hung, Chi Yin Lin, Yen Ju Tsai, Mau Sheng Chen, Fan Tien Cheng

研究成果: Conference article

4 引文 (Scopus)

摘要

In this paper, we design an Auto-scaling Cloud Manufacturing Framework (ACMF), aimed at providing a rapid development paradigm of how to build cloud manufacturing systems for the machine tool industry. First, a worker controller (WCR) is designed to automatically adjust the number of virtual machines according to demands for supporting multiple users to simultaneously access the cloud services using just enough computing resource. Second, a bulletin board-based exchange (BBX) protocol is designed to exchange data through shared cloud storages for reducing the burdens of developing manufacturing system. Further, we develop an Ontology inference cloud service (OICS) as an example of cloud manufacturing system. Two core functional modules, the Ontology inference module and the VMT (Virtual Machine Tool) module, are developed in the OICS for recommending suitable machine tools or cutting tools and performing VMT simulations, respectively. Finally, we deploy the OICS to a public cloud, namely Windows Azure, and apply the OICS to a machine tool factory for conducting integrated tests. Testing results show that the OICS can successfully recommend suitable machine tools or cutting tools for machining tasks, validating its efficacy of acting as a cloud manufacturing service.

原文English
文章編號6899431
頁(從 - 到)893-898
頁數6
期刊IEEE International Conference on Automation Science and Engineering
2014-January
DOIs
出版狀態Published - 2014 一月 1
事件2014 IEEE International Conference on Automation Science and Engineering, CASE 2014 - Taipei, Taiwan
持續時間: 2014 八月 182014 八月 22

指紋

Machine tools
Ontology
Industry
Cutting tools
Bulletin boards
Electronic data interchange
Industrial plants
Machining
Network protocols
Controllers
Testing
Virtual machine

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

引用此文

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abstract = "In this paper, we design an Auto-scaling Cloud Manufacturing Framework (ACMF), aimed at providing a rapid development paradigm of how to build cloud manufacturing systems for the machine tool industry. First, a worker controller (WCR) is designed to automatically adjust the number of virtual machines according to demands for supporting multiple users to simultaneously access the cloud services using just enough computing resource. Second, a bulletin board-based exchange (BBX) protocol is designed to exchange data through shared cloud storages for reducing the burdens of developing manufacturing system. Further, we develop an Ontology inference cloud service (OICS) as an example of cloud manufacturing system. Two core functional modules, the Ontology inference module and the VMT (Virtual Machine Tool) module, are developed in the OICS for recommending suitable machine tools or cutting tools and performing VMT simulations, respectively. Finally, we deploy the OICS to a public cloud, namely Windows Azure, and apply the OICS to a machine tool factory for conducting integrated tests. Testing results show that the OICS can successfully recommend suitable machine tools or cutting tools for machining tasks, validating its efficacy of acting as a cloud manufacturing service.",
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Development of Auto-scaling Cloud Manufacturing Framework for machine tool industry. / Chen, Chao Chun; Lin, Yu Chuan; Hung, Min Hsiung; Lin, Chi Yin; Tsai, Yen Ju; Chen, Mau Sheng; Cheng, Fan Tien.

於: IEEE International Conference on Automation Science and Engineering, 卷 2014-January, 6899431, 01.01.2014, p. 893-898.

研究成果: Conference article

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