The Development of an Artificial Intelligence System for Inventory Management Using Multiple Experts
Abstract
The primary objective of this thesis was to discover the expert decision heuristics for a limited inventory management task. A second objective was to incorporate these heuristics into an expert system and measure the performance level of this expert system, both in terms of the effectiveness and the efficiency of the decision which resulted. A fourteen step approach to the development and testing of expert systems which incorporates many of the lessons learned from past developmental efforts was used. The approach included the use of the Delphi Technique for task and expert selection, the use of multiple experts as a group, and use of the Nominal Group Technique to achieve consensus. Seven experts worked as a group with the researcher to determine the decision heuristics. The expert system which was developed, the Inventory Management Assistant (IMA), contained 441 rules and recommended advice to the user on ten separate elements. The expert system was then tested to determine the effect of the expert system on decision effectiveness and efficiency. Inventory managers who were assisted by the expert system exhibited significant performance improvements on a complex problem.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1986
- Accession Number
- ADA176814
Entities
People
- Mary K. Allen
Organizations
- Air Force Institute of Technology