Turbine Engine Diagnostics (TED)

Authors

  • Richard Helfman
  • Ed Baur
  • John Dumer
  • Tim Hanratty
  • Holly Ingham

DOI:

https://doi.org/10.1609/aimag.v20i1.1441

Abstract

Turbine engine diagnostics (TED) is a diagnostic expert system to aid the M1 Abrams tank mechanic find-and-fix problems in the AGT-1500 turbine engine. TED was designed to provide the apprentice mechanic with the ability to diagnose and repair the turbine engine like an expert mechanic. The expert system was designed and built by the U.S. Army Research Laboratory and the U.S. Army Ordnance Center and School. This article discusses the relevant background, development issues, reasoning method, system overview, test results, return on investment, and fielding history of the project. Limited fielding began in 1994 to select U.S. Army National Guard units and complete fielding to all M1 Abrams tank maintenance units started in 1997 and will finish by the end of 1998. The Army estimates that TED will save roughly $10 million a year through improved diagnostic accuracy and reduced waste. The development and fielding of the TED program represents the Army's first successful fielded maintenance system in the area of AI. Several reasons can be given for the success of the TED program: an appropriate domain with proper scope, a close relationship with the expert, extensive user involvement, and others that are discussed in this article.

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Published

1999-03-15

How to Cite

Helfman, R., Baur, E., Dumer, J., Hanratty, T., & Ingham, H. (1999). Turbine Engine Diagnostics (TED). AI Magazine, 20(1), 69. https://doi.org/10.1609/aimag.v20i1.1441

Issue

Section

Articles