Accession Number : ADP003939

Title :   Application of Artificial Intelligence to Equipment Maintenance,


Personal Author(s) : Hinchman,J. H. ; Morgan,M. C.

Report Date : JUN 1984

Pagination or Media Count : 17

Abstract : All military services are confronted with increased training costs, reduced training budgets and a widening gap between the skills of entry-level personnel and the abilities required to maintain increasingly sophisticated systems. Institutional training is being minimized, and more emphasis is placed on on-the-job training. This requires a greater reliance on built-in test equipment and organic automatic test equipment support. Unfortunately, automated testing (built-in or off-line) does not unambiguously fault-isolate all of the time. The result is a high rate (up to 30%) of removal and replacement of non-faulty assemblies. Reduction of the number of suspected faulty assemblies within an ambiguity group requires manual troubleshooting. The manual troubleshooting procedure used to fault isolate to a single assembly typically involves an exhaustive method of remove-replace-retest. This manual troubleshooting method is expensive in terms of both test time and logistics support. A computer-based intelligent Maintenance Aid offers a solution to this problem. (Author)

Descriptors :   *Artificial intelligence, *Maintenance management, *Electronic equipment, Self contained, Test equipment, Automatic, Prototypes

Distribution Statement : APPROVED FOR PUBLIC RELEASE