Title :
Development of Auto-scaling Cloud Manufacturing Framework for machine tool industry
Author :
Chao-Chun Chen ; Yu-Chuan Lin ; Min-Hsiung Hung ; Chi-Yin Lin ; Yen-Ju Tsai ; Mau-Sheng Chen ; Fan-Tien Cheng
Author_Institution :
Inst. of Manuf. Inf. & Syst., Nat. Cheng Kung Univ., Tainan, Taiwan
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.
Keywords :
cloud computing; cutting tools; inference mechanisms; machine tools; machinery production industries; manufacturing data processing; ontologies (artificial intelligence); production engineering computing; virtual machines; ACMF; BBX protocol; OICS; VMT module; WCR; Windows Azure; auto-scaling cloud manufacturing framework; bulletin board-based exchange protocol; cloud services; cutting tools; data exchange; machine tool factory; machine tool industry; ontology inference cloud service; ontology inference module; rapid development paradigm; shared cloud storages; virtual machine tool module; virtual machines; worker controller; Cloud computing; Computer numerical control; Machine tools; Manufacturing systems; Ontologies; Virtual machining;
Conference_Titel :
Automation Science and Engineering (CASE), 2014 IEEE International Conference on
Conference_Location :
Taipei
DOI :
10.1109/CoASE.2014.6899431