Article ID: | iaor20062395 |
Country: | United Kingdom |
Volume: | 56 |
Issue: | 8 |
Start Page Number: | 912 |
End Page Number: | 921 |
Publication Date: | Aug 2005 |
Journal: | Journal of the Operational Research Society |
Authors: | Edwards J.S., Robinson S., Alifantis T., Ladbrook J., Waller A. |
Keywords: | simulation, artificial intelligence, knowledge management |
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.