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Navigating the Production Maze: The Topic Mapped Enterprise

Paper, was published by James David Mason and Thomas M. Insalaco at 2004-08-02

This paper proposes a topic map that is able to treat a specific product line in depth.

External Link: download slides

A manufacturing enterprise is an intricate web of links among products, their components, their materials, and the facilities needed to turn materials into components and completed products. Facilities, full of equipment, also depend on trained staff for operation. The Y-12 National Security Complex, owned by the U.S. Department of Energy, has a rather specialized product line, but its problems are typical of large-scale manufacturing in many high-tech industries. Faced with the need to maintain products that may have been built decades ago, Y-12 needs to develop a system that can rapidly find out what tools are needed to make parts for a particular product or, if tools are replaced, which products will be affected. Our proposed solution is a topic map that treats our products in detail, the component flows, and the facilities and tools available in the Complex. We hope to extend this map to include other aspects of our operations, including the skills and staffing levels necessary to operate our processes. Although the Topic Map is still in preliminary development, we are already learning new things about our enterprise from it.

Authors

James David Mason

No contact information available. 

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James David is author of Topic Maps for Managing.. , Ferrets and Topic Maps:.. , Navigating the Production.. , Fine-grained publications.. , and Why not a Topic Map?.

Thomas M. Insalaco

No contact information available. 

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Thomas M. is author of Navigating the Production.. .

 

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As a former information scientist, I am fascinated since 1999 by the capabilities for building Topic Maps-based knowledge systems having the potential to augment human mind. One can model arbitrary knowledge organization systems, deal with semantic heterogeneity, collocate all facts about one subject in one logical place, and with TMQL have semantic retrieval on federated semantic networks. Therefore I expect bright prospects for business concepts building on the exchange of such knowledge snippets via semantic knowledge services.

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