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.
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This work was jointly funded by the EPSRC (Grant reference GR/M72876), Ford Motor Company and the Lanner Group.
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Robinson, S., Alifantis, T., Edwards, J. et al. Knowledge-based improvement: simulation and artificial intelligence for identifying and improving human decision-making in an operations system. J Oper Res Soc 56, 912–921 (2005). https://doi.org/10.1057/palgrave.jors.2601915
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DOI: https://doi.org/10.1057/palgrave.jors.2601915