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

S Robinson (), T Alifantis (), J S Edwards, J Ladbrook and A Waller
Additional contact information
S Robinson: University of Warwick
T Alifantis: University of Warwick
J S Edwards: Aston University
J Ladbrook: Ford Motor Company, Dunton Engineering Centre (15/4A-F04-D), Laindon, Basildon
A Waller: Lanner Group, The Oaks

Journal of the Operational Research Society, 2005, vol. 56, issue 8, 912-921

Abstract: Abstract 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.

Keywords: simulation; artificial intelligence; human decision-making; knowledge elicitation; expert system (search for similar items in EconPapers)
Date: 2005
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Citations: View citations in EconPapers (2)

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DOI: 10.1057/palgrave.jors.2601915

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