Improving the design process for factories: modelling human performance variation

Steve Mason, Tim Baines, John M. Kay, John Ladbrook

Research output: Contribution to journalArticlepeer-review


Theprocess of manufacturing system design frequently includes modeling, and usually, this means applying a technique such as discrete event simulation (DES). However, the computer tools currently available to apply this technique enable only a superficial representation of the people that operate within the systems. This is a serious limitation because the performance of people remains central to the competitiveness of many manufacturing enterprises. Therefore, this paper explores the use of probability density functions to represent the variation of worker activity times within DES models.
Original languageEnglish
Pages (from-to)47-54
Number of pages8
JournalJournal of Manufacturing Systems
Issue number1
Publication statusPublished - 2005

Bibliographical note

NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Manufacturing Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Mason, S, Baines, T, Kay, JM & Ladbrook, J, 'Improving the design process for factories: modelling human performance variation' Journal of manufacturing systems, vol. 24, no. 1 (2005) DOI


  • simulation
  • human performance modeling
  • human performance variation


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