Experimental Verification of End-Milling Condition Decision Support System Using Data-Mining for Difficult-to-Cut Materials
Experimental Verification of End-Milling Condition Decision Support System Using Data-Mining for Difficult-to-Cut Materials
复制标题
难切削材料端铣条件决策支持系统数据挖掘实验验证
DOI：
10.4028/www.scientific.net/amr.1017.334
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
K. Okuda
中科院分区：
文献类型：
--
作者：
Hiroyuki Kodama;T. Hirogaki;E. Aoyama;K. Ogawa;K. Okuda
提出了基于层次聚类和非层次聚类的数据挖掘方法，可帮助制造工程师确定端铣加工条件的决策准则。我们已经构建了一个新的系统，使用聚类技术和工具目录数据，以支持确定端铣条件为不同类型的最近难以切割的材料。在本报告中，我们特别关注切割速度来评估该系统的性能。与日本著名刀具制造商推荐的条件进行比较，表明我们提出的系统可用于确定各种难切削材料的切削速度。也就是说，在两组端铣条件（从端铣条件决策支持系统导出的条件和专家工程师建议的条件）下，对于难切削材料（奥氏体不锈钢; JIS SUS 310），使用方形端铣刀的铣削实验表明，目录挖掘方法对于导出用于在制造阶段开始时决定端铣条件的准则是有效的。
Data-mining methods using hierarchical and non-hierarchical clustering are proposed, which could help manufacturing engineers determine guidelines for deciding end-milling conditions. We have constructed a novel system that uses clustering techniques and tool catalog data to support the determination of end-milling conditions for different types of recent difficult-to-cut materials. In the present report, we especially focus on the cutting speed to estimate the performance of this system. A comparison with the conditions recommended by famous tool makers in Japan, reveals that our proposed system can be used to determine the cutting speeds for various difficult-to-cut materials. That is, milling experiments using a square end mill under two sets of end-milling conditions (conditions derived from the end-milling condition decision support system and conditions suggested by expert engineers) for difficult-to-cut materials (austenite stainless steel; JIS SUS310) showed that the catalog mining method is effective for deriving guidelines for deciding end-milling conditions at the beginning of the manufacturing stage.