Development of Machine-Tool Recommendation Cloud Service based on Ontology Inference Technology for Machine Tool Industry

• Main Authors: Chih-YinLin, 林芝吟
• Other Authors: Chao-Chun Chen
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/23j6xh

碩士 === 國立成功大學 === 製造資訊與系統研究所 === 102 === In this paper, we design and implement an Ontology Inference Cloud Service (OICS) system and a cloud-based auto scaling mechanism. The OICS system provides Ontology inference-based machine tool recommended service, so that manufacturing process engineers can use OICS to find suitable cutting tools for cutting the specified workpiece. For supporting multi-user scenarios, the OICS can dynamically scale up and down cloud resources according to the pre-defined scaling rules. In addition, the core mechanism of cloud-based ontology inference can publish standalone packages (such as virtual machine tool package) as cloud services on the cloud platform, so that developers can integrate existing manufacturing packages in the OICS system to shorten the development period. In this thesis, we first describe the system framework of Ontology Inference Cloud Service. Secondly, we present the core mechanisms of the OICS system. Thirdly, we develop and build the OICS system in Azure, the public cloud platform of Microsoft Corp. Our system can provide users to create ontology Inference data and rules and inference on the Ontology data for finding out proper cutting tools. Finally, in the experiment, we use two scenarios to verify OICS feasibility and performance evaluation. This paper provides the use of cloud computing and Ontology inference systems for building a new knowledge application in the machine tool industry.