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Applications of MFM to intelligent systems for supporting plant operators and designers:function-based inference techniques GOFUKU Akio
Graduate School of Natural Science and Technology, Okayama University,
3-1-1, Tsushima-Naka, Kita-ku, Okayama, 700-8530 Japan (fukuchan@sys.okayama-u.ac.jp) Abstract:An artifact is designed based on the intention of designers. The functional information is a description of an artifact in a high level of abstraction. It represents the designers’ intention by explaining why a component exists in a system. A human tries to understand an artifact or an event that is new for him/her by changing his/her viewpoints and abstraction levels. Representing functional information is important in understanding an anomalous situation of a system, finding a plausible way to solve a problem when the counter actions prepared are not successfully used in some reason, and designing an artifact. This article first introduces the conception of function, the outline of the MFM that is a functional modeling framework, and an MFM model the authors developed. Thereafter, three function-based inference techniques based on a model by the MFM are presented. The applications of the three techniques and the findings obtained from the studies by authors will be presented in another article.
Keyword: function; multi-level flow modeling; function-based inference; causality estimation; function flow simplification; explanation generation |
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