合金開発を支援するための実験データマイニングと知識マネジメント・システム(一般セッションI)

概要

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In alloy development, the experimental data is so huge and wide-ranging as to do for new development directly. In this research, I propose a design supporting system for the development of new aluminum alloy which extracts new necessary knowledge from the huge experimental data. To be more precise, this system divides alloys into clusters with a rule of manufacturing conditions at customers' request and forecasts unknown alloys' conditions of production with the use of change matrix. This change matrix indicates transmutations of conditions of production between alloy clusters. With this, we can forecast not only required alloy's conditions of production as the neighborhood of base alloy but also their changes from almost all alloys.
社団法人日本機械学会の論文
2004-11-29