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Cognitive engineering for decision support modeling of diagnostic tasks in a complex system

In this paper, a new approach to diagnostic support modeling of a complex system maintenance process is described. From cognitive engineering perspective, methods for decomposing complex maintenance problems are developed. The "methods" are represented as intelligent diagnostic agents for use in a system level maintenance reasoning. Sample simulation results show that cognitive engineering driven diagnostic reasoning has higher performance reliability than the traditional rule-based (simulation) diagnostic systems.