Mining SOTs and dispatching rules from RFID-enabled real-time shopfloor production data

Ray Y. Zhong, George Q. Huang, Q. Y. Dai, T. Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

71 Citations (Scopus)


Radio frequency identification (RFID) has been widely used in manufacturing field and created a ubiquitous production environment, where advanced production planning and scheduling (APS) might be enabled. Within such environment, APS usually requires standard operation times (SOTs) and dispatching rules which have been obtained from time studies or based on past experiences. Wide variations exist and frequently cause serious discrepancies in executing plans and schedules. This paper proposes a data mining approach to estimate realistic SOTs and unknown dispatching rules from RFID-enabled shopfloor production data. The approach is evaluated by real-world data from a collaborative company which has been used RFID technology for supporting its shopfloor production over seven years. The key impact factors on SOTs are quantitatively examined. A reference table with the mined precise and practical SOTs is established for typical operations and suitable dispatching rules are labled as managerial implicities, aiming at improving the quality and stability of production plans and schedules.

Original languageEnglish
Pages (from-to)825-843
Number of pages19
JournalJournal of Intelligent Manufacturing
Issue number4
Publication statusPublished - Aug 2014
Externally publishedYes


  • Advanced Production Planning and Scheduling (APS)
  • Data mining
  • Dispatching rules
  • Radio Frequency Identification (RFID)
  • Real-time
  • Standard Operation Times (SOTs)

ASJC Scopus subject areas

  • Software
  • Industrial and Manufacturing Engineering
  • Artificial Intelligence


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