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Flexible Automation and Integrated Manufacturing 1994

ISBN 打印: 978-1-56700-018-4

A KNOWLEDGE-BASED SYSTEM APPROACH TO BENCHMARKING THE TRANSITION TO AGILE MANUFACTURING

Abstract

The role of artificial intelligence (AI) in manufacturing applications such as agile manufacturing (AM) is a subject of critical importance to efficient and effective information management. The subset of AI with the greatest potential to make a significant contribution to the management of information is knowledge-based systems (KBS); which is a focal point of the research contained in this paper.
AM is a rapidly developing methodology of competitive revitalization for the manufacturing sector of the American economy. AM seeks to integrate and synthesize many concepts and theories which have, when implemented in virtual isolation, provided some promise of competitive advantage. A significant dilemma for AM, however, is that few tangible tools have been provided to manufacturers which would manage the flow of information necessary to guide the process of transitioning. The KBS developed for and discussed in this paper, AM-CHECK, will provide that guidance through an innovative integration of two problem-solving methodologies.
The two problem-solving methodologies which have been integrated are structured matching and candidate evaluation. Integration of these methodologies has enabled an operational prototype KBS to be created, AM-CHECK which has the ability to process qualitative as well as quantitative data. The implication of a contribution to primary research in AI applications is that an entirely new set of problem-solving algorithms will be available for implementation where there had previously been no tools with the inherent capability.
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