RFID-enabled real-time manufacturing information tracking infrastructure for extended enterprises

Yingfeng Zhang, Pingyu Jiang, George Huang, Ting Qu, Guanghui Zhou, Jun Hong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

57 Citations (Scopus)

Abstract

In extended enterprises, real-time manufacturing information tracking plays an important role and aims to provide the right information to the right person at the right time in the right format to achieve optimal production management among the involved enterprises. However, many enterprises are caused by lack of timely, accurate and consistent manufacturing data. The laggard information transfer flow and the unmatched information transfer method bring extended enterprises much more uncertainty and unknowingness. This paper proposes a RFID-enabled real-time manufacturing information tracking infrastructure (RTMITI) to address the real-time manufacturing data capturing and manufacturing information processing methods for extended enterprises. Following the proposed infrastructure, the traditional manufacturing resources such as employees, machines and materials are equipped with RFID devices (Readers and Tags) to build the real-time data capturing environment. In addition, a series of manufacturing information processing methods are established to calculate and track the real-time manufacturing information such as realtime manufacturing cost, progress, WIP (Work-in-progress) inventory etc. in parts/assemblies/ products at machines/shop floors/enterprises/ extended enterprises levels. Finally, a case study is given to demonstrate the developed framework and corresponding methodologies.

Original languageEnglish
Pages (from-to)2357-2366
Number of pages10
JournalJournal of Intelligent Manufacturing
Volume23
Issue number6
DOIs
Publication statusPublished - Dec 2012
Externally publishedYes

Keywords

  • Extended enterprises
  • Information tracking
  • Real-time manufacturing
  • RFID

ASJC Scopus subject areas

  • Software
  • Industrial and Manufacturing Engineering
  • Artificial Intelligence

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