Abstract
Evaluation models of automatic diagnostic systems are investigated taking into consideration their imperfections such as failure to diagnose, incorrect isolation, false alarms, and inability to duplicate. Three measures of effectiveness are developed that enable the decision-maker to assess accurately the real capability of the diagnostic system and to evaluate and compare the performances of alternative automatic diagnostic systems based on their mean life-cycle cost. Analytic procedures for using these measures are developed, and an example is presented. It is concluded that the capability and performance of automatic diagnostic systems can be assessed using three measures of effectiveness; false removal, failure to diagnose, and false alarm correction. The three measures can be used to predict the mean life-cycle cost of automatic diagnostic systems, including the mean cost of imperfections of such systems. >
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