TURBINE ENGINE DIAGNOSTICS (TED) is a diagnostic expert system to aid the M
1 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 d
iagnose and repair the turbine engine like an expert mechanic. The expert s
ystem 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 ba
ckground, development issues, reasoning method, system overview, test resul
ts, return on investment, and fielding history of the project. Limited fiel
ding began in 1994 to select U.S. Army National Guard units and complete fi
elding to all M1 Abrams tank maintenance units started in 1997 and will fin
ish by the end of 1998. The Army estimates that TED will save roughly $10 m
illion a year through improved diagnostic accuracy and reduced waste. The d
evelopment and fielding of the TED program represents the Army's first succ
essful fielded maintenance system in the area of AI. Several reasons can be
given for the success of the TED program: an appropriate domain with prope
r scope, a close relationship with the expert, extensive user involvement,
and others that are discussed in this article.