Resequencing and feature assignment on an automated assembly line

Maher Lahmar, Hakan Ergan, Saif Benjaafar

Research output: Contribution to journalArticlepeer-review

46 Scopus citations


We consider the problem of resequencing a prearranged set of jobs on a moving assembly line with the objective of minimizing changeover costs. A changeover cost is incurred whenever two consecutive jobs do not share the same feature. Features are assigned from a set of job-specific feasible features. Resequencing is limited by the availability of offline buffers. The problem is motivated by a vehicle resequencing and painting problem at a major U.S. automotive manufacturer. We develop a model for solving the joint resequencing and feature assignment problem and an efficient solution procedure for simultaneously determining optimal feature assignments and vehicle sequences. We show that our solution approach is amenable to implementation in environments where a solution must be obtained within tight time constraints. We also show that the effect of offline buffers is of the diminishing kind with most of the benefits achieved with very few buffers. This means that limited resequencing flexibility is generally sufficient. Furthermore, we show that the value of resequencing is sensitive to the feature density matrix, with resequencing having a significant impact on cost only when density is in the middle range.

Original languageEnglish (US)
Pages (from-to)89-102
Number of pages14
JournalIEEE Transactions on Robotics and Automation
Issue number1
StatePublished - Feb 2003

Bibliographical note

Funding Information:
Manuscript received November 12, 2001; revised April 28, 2002. This paper was recommended for publication by Associate Editor C. Chu and Editor N. Viswanadham upon evaluation of the reviewers’ comments. This work was supported in part by the National Science Foundation under Grant DMII-9908437 and in part by the Ford Motor Company.


  • Assembly line design
  • Feature assignment
  • Sequencing with setups


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