Improving the design process for factories:modelling human performance variation


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.

Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
Additional Information: 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
Publication ISSN: 1878-6642
Last Modified: 29 Nov 2023 10:06
Date Deposited: 15 Aug 2012 13:30
Full Text Link: 10.1016/S0278-6125(05)80006-8
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PURE Output Type: Article
Published Date: 2005
Authors: Mason, Steve
Baines, Tim
Kay, John M.
Ladbrook, John



Version: Accepted Version

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