The general motors variation-reduction adviser: deployment issues for an AI application

  • Authors:
  • Alexander P. Morgan;John A. Cafeo;Kurt Godden;Ronald M. Lesperance;Andrea M. Simon;Deborah L. McGuinness;James L. Benedict

  • Affiliations:
  • GM R&D Center, Manufacturing Systems Research Lab, Warren, MI;GM R&D Center, Vehicle Analysis and Dynamics Lab, Warren, MI;GM R&D Center, Manufacturing Systems Research Lab, Warren, MI;GM R&D Center, Manufacturing Systems Research Lab, Warren, MI;GM R&D Center, Manufacturing Systems Research Lab, Warren, MI;McGuinness Associates, Stanford, CA;McGuinness Associates, Stanford, CA

  • Venue:
  • IAAI'04 Proceedings of the 16th conference on Innovative applications of artifical intelligence
  • Year:
  • 2004

Quantified Score

Hi-index 0.00

Visualization

Abstract

The General Motors Variation-Reduction Adviser is a knowledge system built on case-based reasoning principles that is currently in use in a dozen General Motors Assembly Centers. This paper reviews the overall characteristics of the system and then focuses on various AI elements critical to support its deployment to a production system. A key AI enabler is ontology-guided search using domain-specific ontologies.