Knowledge based improvement:simulation and artificial intelligence for identifying and improving human decision-making in an operations systems


The performance of most operations systems is significantly affected by the interaction of human decision-makers. A methodology, based on the use of visual interactive simulation (VIS) and artificial intelligence (AI), is described that aims to identify and improve human decision-making in operations systems. The methodology, known as 'knowledge-based improvement' (KBI), elicits knowledge from a decision-maker via a VIS and then uses AI methods to represent decision-making. By linking the VIS and AI representation, it is possible to predict the performance of the operations system under different decision-making strategies and to search for improved strategies. The KBI methodology is applied to the decision-making surrounding unplanned maintenance operations at a Ford Motor Company engine assembly plant.

Publication DOI:
Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
Additional Information: This is a post-peer-review, pre-copied its version of an article published in Journal of the Operational Research Society]. The definitive publisher-authenticated version Robinson, S., Alifantis, T., Edwards, J. S., Ladbrook, J., & Waller, A. (2005). Knowledge based improvement: simulation and artificial intelligence for identifying and improving human decision-making in an operations systems. Journal of the Operational Research Society, 56(8), 912-921 is available online at:
Uncontrolled Keywords: simulation,artificial intelligence,human decision-making,knowledge elicitation,expert system
Publication ISSN: 1476-9360
Last Modified: 23 May 2024 07:07
Date Deposited: 30 Oct 2009 15:17
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Related URLs: http://www.palg ... l/2601915a.html (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2005-08
Authors: Robinson, S.
Alifantis, T.
Edwards, J.S. (ORCID Profile 0000-0003-3979-017X)
Ladbrook, J.
Waller, A.



Version: Accepted Version

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