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The development of knowledge-based expert systems requires the understanding and regulation of several complex tasks. The key to the successful application of knowledge-based expert systems lies in understanding how the various components affect the system's overall performance. Effectively understanding the interrelationships among components of an expert system and the role that each component plays is important. The knowledge base in the expert system serves as a storehouse of knowledge primitives including the basic facts, domain theories, production rules, and heuristics available to the system. An expert system cannot be a valuable domain problem solver if the knowledge base does not contain the required quantitive and qualitive knowledge. A problem often cited in the implementation of knowledge-based expert systems is the knowledge acquisition bottleneck. Consequently, the elicitation of knowledge from knowledge sources becomes important. It is a time consuming component of the expert system development life-cycle. Therefore, the design and development of a prototype Knowledge Acquisition (KA) facility (or KA tool) to overcome this problem will definitely help facilitate the development of knowledge-based expert systems.

The forms in which knowledge is elicited from a human expert may not always match the forms in which it is used by a knowledge-based expert system. The selection of a knowledge representation technique to represent different types of human knowledge depends on the analysis of knowledge sources. Consequently, designing a functional KA facility to extract domain knowledge from knowledge sources, transforming the knowledge gained into the system's knowledge, refining the venerated knowledge, validating and verifying the refined knowledge, and storing the validated and verified knowledge into a format compatible to the system's knowledge base structure is a complicated task.

A prototype knowledge acquisition system for fuzzy knowledge base development was designed and developed in this research. This tool assists in the acquisition of domain knowledge and in the generation of domain knowledge bases. The surface mount PWB assembly arena was a focus of this research. The prototype system serves as a knowledge base generator with the ability to collect knowledge and data, represent intermediate knowledge and data, and store knowledge and data. To attain the stated research objectives, this research employed the principles of designing knowledge based systems, knowledge acquisition mechanisms, methods and techniques of knowledge acquisition, and fuzzy set theory and fuzzy logic.


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