OICS: A knowledge-based cloud manufacturing system for machine tool industry

Chih Yin Lin, Yen Ju Tsai, Hsuan Chun Lin, Chao Chun Chen

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

In this paper, an Ontology inference cloud service (OICS) with auto-scaling capability is designed and implemented for the CNC machine tool industry. The OICS is a knowledge-based cloud manufacturing system, and is used to recommend machine tools and cutting tools based on the Ontology inference techniques. Three core functional modules: the Ontology inference module, the VMT (Virtual Machine Tool) module, and the request filtering module, are developed to allow multiple users to perform inference service, and verify the recommended machine tools or cutting tools via VMT simulations. The OICS is implemented and hosted in a cloud virtual machine, called a worker. Furthermore, the worker controller (WCR), is designed to automatically adjust the number of virtual machines to provide users splendid service quality. Finally, we deploy the developed OICS to a public cloud platform, namely Windows Azure, to conduct integrated tests. Testing results of a case study physically applying the OICS to a machine tool factory show that the OICS can successfully recommend suitable machine tools and cutting tools for machining tasks, and support multiple users in a reasonable performance. The results of this paper can be a useful reference for industrial practitioners to construct cloudbased manufacturing systems.

Original languageEnglish
Pages (from-to)92-99
Number of pages8
JournalSmart Science
Volume3
Issue number2
DOIs
Publication statusPublished - 2015

All Science Journal Classification (ASJC) codes

  • Chemistry (miscellaneous)
  • Modelling and Simulation
  • Energy (miscellaneous)
  • Engineering(all)
  • Fluid Flow and Transfer Processes
  • Computer Networks and Communications
  • Computational Mathematics

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