Expert Systems and Engineering Design Knowledge

Abstract

 Of all the contributions of artificial intelligence (AI), expert systems show some of the most significant promise for engineering applications. An expert system provides a framework for acquiring, representing, and using knowledge about a particular application's domain. The role of knowledge in engineering design merits closer attention so that AI-oriented computer-aided engineering (CAE) systems can be developed and maintained systematically. Because'knowledge'in engineering applications is loosely defined, it is necessary to identify knowledge types and the correlations between them before widespread engineering design applications can be achieved. The types of domain knowledge, facts, procedures, judgments, and control, differ from the classes of that knowledge, creative, innovative, and routine. Feasible engineering tasks for expert systems can be determined based on these types and classes of knowledge. Prototype expert systems have been developed for civil engineering applications to assist with interpretation, design, planning, diagnosis, control, and other engineering system functions. A number of these are described herein. Interpretive tasks require reasoning about a task in light of the knowledge available, while generative tasks create potential solutions to be tested against constraints. Only after classifying the domain by type and level can the engineer select an appropriate knowledge-engineering tool for the domain being considered. The critical features to be weighed after problem classification are knowledge representation techniques, control strategies, interface requirements, compatibility with traditional systems, and economic considerations. After considering all of these factors in the selection of the expert system took, the engineer can then proceed with the acquisition of knowledge and the construction and use of the expert syste