Optimal layout and work allocation in batch assembly under learning effect

Yuval Cohen, Ezey M. Dar-El, Gad Vitner, Subhash Sarin

Research output: Contribution to journalArticlepeer-review


This research investigates the effect of system’s configuration (layout) and work allocation on the makespan of batches of different products characterised by significant learning. Frequently, in science-based industries the layout of the batch assembly could be relatively easily setup separately for each batch, where each batch contains different type of products. The research aims at finding guidelines for configurations and work allocations that will minimise the makespan for a given number of workers. Analytical expression of the makespan is developed and analysed.

Original languageEnglish
Pages (from-to)188-207
Number of pages20
JournalInternational Journal of Intelligent Systems Technologies and Applications
Issue number1-2
StatePublished - 2008


  • assembly line
  • batch assembly
  • industrial learning
  • layout
  • makespan
  • work allocation


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