Journal of the Operational Research Society

, Volume 56, Issue 8, pp 912–921 | Cite as

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
  • A Waller
Case-Oriented Paper

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 

Notes

Acknowledgements

This work was jointly funded by the EPSRC (Grant reference GR/M72876), Ford Motor Company and the Lanner Group.

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Copyright information

© Palgrave Macmillan Ltd 2004

Authors and Affiliations

  • S Robinson
    • 1
  • T Alifantis
    • 1
  • J S Edwards
    • 2
  • J Ladbrook
    • 3
  • A Waller
    • 4
  1. 1.University of WarwickCoventryUK
  2. 2.Aston UniversityBirminghamUK
  3. 3.Ford Motor Company, Dunton Engineering Centre (15/4A-F04-D), Laindon, BasildonEssexUK
  4. 4.Lanner Group, The OaksWorcestershireUK

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