Abstract
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 language | English |
|---|---|
| Pages (from-to) | 47-54 |
| Number of pages | 8 |
| Journal | Journal of Manufacturing Systems |
| Volume | 24 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 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 http://dx.doi.org/10.1016/S0278-6125(05)80006-8Keywords
- simulation
- human performance modeling
- human performance variation