Lot streaming for product assembly in job shop environment

F.T.S. Chan, T.C. Wong, L.Y. Chan

Research output: Contribution to journalArticle

48 Citations (Scopus)

Abstract

Assembly job shop scheduling problem (AJSP) is an extension of classical job shop scheduling problem (JSP). AJSP starts with JSP and appends an assembly stage to the completed jobs. Lot streaming (LS) technique is a process of splitting jobs into smaller sub-jobs such that successive operations can be overlapped. This paper combines, for the first time, LS and AJSP, extending LS applicability to both machining and assembly. To solve this complex problem, an efficient algorithm is proposed using genetic algorithms and simple dispatching rules. Experimental results suggest that equal size LS outperforms varied size LS with respect to the objective function.
Original languageEnglish
Pages (from-to)321-331
Number of pages11
JournalRobotics and Computer Integrated Manufacturing
Volume24
Issue number3
DOIs
Publication statusPublished - 1 Jun 2008

Fingerprint

Lot Streaming
Job Shop Scheduling Problem
Job Shop
Dispatching Rules
Machining
Efficient Algorithms
Objective function
Genetic algorithms
Job shop scheduling
Genetic Algorithm
Experimental Results

Keywords

  • lot streaming
  • product assembly
  • job shop
  • environment
  • genetic algorithms
  • dispatching rules

Cite this

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Lot streaming for product assembly in job shop environment. / Chan, F.T.S.; Wong, T.C.; Chan, L.Y.

In: Robotics and Computer Integrated Manufacturing, Vol. 24, No. 3, 01.06.2008, p. 321-331.

Research output: Contribution to journalArticle

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