Modeling diagnostic constraints with AI-ESTATE

The Artificial Intelligence and Expert System Tie to Automatic Test Equipment (AI-ESTATE) subcommittee of the IEEE Standards Coordinating Committee 20 (SCC20) has been developing a set of standards for exchanging diagnostic knowledge in intelligent test systems. To date, AI-ESTATE has developed models for fault trees and enhanced diagnostic inference models (EDIMs). Since the start of committee work, it was believed that AI-ESTATE needed to address the issue of defining constraint knowledge, which could be used to guide and refine diagnostics. In this paper, we discuss early efforts by AI-ESTATE to define such a constraint model.