Integrating order review/release and dispatching rules for assembly job shop scheduling using a simulation approach

H. L. Lu, George Q. Huang, H. D. Yang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

84 Citations (Scopus)

Abstract

This paper deals with an assembly job shop scheduling problem considering two phases of control: order review/release (ORR) and dispatching rules. Dispatching rules have been intensively used in earlier job shop research. Such rules determine the processing sequence of jobs waiting in the queues of corresponding machines. In recent years, ORR emerges as another option for job shop control and has received increasing attention. Such control determines when to release jobs to the shop floor. Different ORR mechanisms have been devised and are reported to bring several advantages such as reduced inventory cost of early finished orders, controlled and balanced shop load levels and shorter order flow time. Previous studies on ORR often assume a simplified job shop without assembly operations, while this research applies ORR to an assembly job shop. The aim of this research is to evaluate the ability of different combinations of ORR-dispatching rules in optimising due date and flow time related performance measures. Full factorial experiment has been designed for a simulated assembly job shop. Results show that both ORR and dispatching rules are highly relevant with respect to the due date and flow time related performance measures. Particularly, the incorporation of ORR control into the existing control of dispatching rules is highly important for better performance of assembly job shop control.

Original languageEnglish
Pages (from-to)647-669
Number of pages23
JournalInternational Journal of Production Research
Volume49
Issue number3
DOIs
Publication statusPublished - 1 Feb 2011
Externally publishedYes

Keywords

  • assembly job shop
  • dispatching rules
  • order review/release
  • ORR
  • work load control

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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