Cloud manufacturing based service encapsulation and optimal configuration method for injection molding machine

Yingfeng Zhang, Dong Xi, Haidong Yang, Fei Tao, Zhe Wang

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

This paper aims to introduce the concept of cloud manufacturing (CMfg) in the injection molding industry. The CMfg platform for injection molding enterprises is built to improve the sharing, circulation and integration of the injection molding resources. With the implementation of the Internet of Things technologies in the traditional injection molding shop, the real-time manufacturing information of resources can be accurately captured and the entire molding process becomes more visible and traceable. The virtual machining service of the injection molding machine is encapsulated as a cloud service that published into the platform for on-demand use. When task orders are published, through the presented task-driven proactive service discovery method, competent services can be quickly found. The custom-oriented evaluation method based on technique for order preference by similarity to ideal solution is designed to help the demanders to find satisfying services according to their customized criteria. Since the task orders arrive dynamically, after these orders are assigned to the specified machine, a real-time order dispatching mechanism is developed to provide an optimal scheduling plan for the cloud service. Finally, the proposed framework and methods are illustrated by a numerical simulation.

Original languageEnglish
Pages (from-to)2681-2699
Number of pages19
JournalJournal of Intelligent Manufacturing
Volume30
Issue number7
DOIs
StatePublished - 1 Oct 2019

Keywords

  • Cloud manufacturing
  • Injection molding machine
  • Optimal scheduling
  • Proactive discovery
  • Service evaluation

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