Turbine Engine Diagnostics (TED) is a diagnostic expert system to aid the Ml Abrams tank mechanic find and fix problems in the AGT-1500 turbine engine. TED was designed to provide the apprentice mechanic 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 Schooi (OCandS). This paper 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 Army National Guard units, and complete fielding to all Ml 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 per 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. There are several reasons associated with the success of the TED program: an appropriate domain with proper scope, a close relationship with the expert, extensive user involvement, plus others that are discussed in this paper.