書誌事項
- タイトル別名
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- Proposal of data mining process for tool catalog data introducing machine learning
抄録
<p>We attempt to construct a novel technology development utilizing big data such as Deep Learning in the manufacturing industry. Especially, we look at the data mining method and the tool catalog as a useful big data base which is updated by tool makers because it is easy for CAD/CAM engineers and machine tool operators to obtain it in the manufacturing fields. In the present report, we proposed the visualization and consideration of cutting condition determination process based on a decision tree method which is one type of statistical analysis method for radius-endmill data base. We also developed a cutting condition prediction system with a random forest which is a type of machine learning method applying a decision tree. Moreover, we performed a case study in endmilling under deriving cutting conditions by the proposed method, which is an unknown and expanded cutting condition based on tool catalog data base. As a result, it is demonstrated that the support based on machine learning is found to be effective to select a cutting condition including an unknown cutting condition in tool catalog data base.</p>
収録刊行物
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- 日本機械学会論文集
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日本機械学会論文集 85 (877), 19-00215-19-00215, 2019
一般社団法人 日本機械学会
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詳細情報 詳細情報について
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- CRID
- 1390282752331276160
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- NII論文ID
- 130007711794
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- ISSN
- 21879761
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- Crossref
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可