Functional conflict resolution in automated knowledge generation


In the past decade, the use of control and diagnostic reasoning systems in different areas of government, industry, and university operations has increased. A great number of these systems find their basis in engineering, specifically in process control. The majority of the time devoted to the development of these systems is spent in the areas of Knowledge Engineering (KE) and Knowledge Acquisition (KA). Extensive research for the development of systems that perform the KE task is underway. The work presented here is an approach toward automatic knowledge acquisition. The objective of this research was to construct a complete knowledge base for a diagnostic and control reasoning system from information that resides in Computer Aided Design (CAD) databases. The purpose of CAD is to electrically order the components of a physical system under the direction of a human operator. However, the majority of designs in CAD databases do not contain any knowledge about the flow and operation of the systems they represent; they are simply electronically-stored drawings. It is also possible that the information that does reside in the CAD system is not complete or accurate enough to directly generate a viable knowledge base for an automated reasoning system. An algorithm was developed that automatically generates missing information and corrects potential mistakes made by the CAD draftsperson by using novel constraint labeling techniques. This work will decrease the amount of time spent in the generation of the knowledge base for diagnostic reasoning systems. It will also make possible the creation of more reliable knowledge bases since less hand coding will be required. Because validation and verification are inherent in the automated knowledge acquisition process, it is possible that this work could be expanded to be used as a designer's aide to monitor the draftsperson's activities during CAD drawing development.


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Graduation Date





Myler, Harley R.


Doctor of Philosophy (Ph.D.)


College of Engineering


Computer Engineering




191 p.



Length of Campus-only Access


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Doctoral Dissertation (Open Access)




Dissertations, Academic -- Engineering; Engineering -- Dissertations, Academic

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