Task-driven e-manufacturing resource configurable model

Yingfeng Zhang, Pingyu Jiang, George Q. Huang, T. Qu, Jun Hong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

8 Citations (Scopus)

Abstract

Manufacturing resource configuration (MRC) plays a very important role in an e-Manufacturing system. Higher requirements for optimal configuration under online resource visibility and traceability have led to two main challenges. One is that more features of manufacturing tasks affecting the optimization results should be taken into considerationwhen establishing theMRCmathematical model for a manufacturing cell. The other is that manufacturing information should be given equal attention as MRC to realize realtime visibility and traceability of the resultingmanufacturing cells. This paper presents a comprehensive mathematical model which considers more practical features of manufacturing tasks (e.g. batch volume and alternative processing routes) for manufacturing cell formation. This model adopts a fuzzy clustering method to group the manufacturing tasks and machines. Moreover, it is enabled by a smart equipment model to realize the configurable model of real-time manufacturing information and corresponding visualization and tracing methods. A case study is given to demonstrate the proposed models and methods.

Original languageEnglish
Pages (from-to)1681-1694
Number of pages14
JournalJournal of Intelligent Manufacturing
Volume23
Issue number5
DOIs
Publication statusPublished - Oct 2012
Externally publishedYes

Keywords

  • E-Manufacturing
  • E-Manufacturing cell
  • Real-time manufacturing
  • RFID
  • Traceability and visibility

ASJC Scopus subject areas

  • Software
  • Industrial and Manufacturing Engineering
  • Artificial Intelligence

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