2017 Fiscal Year Final Research Report
Development of Optimization Technique for Difficult-to-cut Material Processing Technology Using Tool Catalog Data-mining System
| Project/Area Number |
15K17952
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Production engineering/Processing studies
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| Research Institution | Okayama University (2017)
University of Hyogo (2015-2016) |
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Principal Investigator |
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Keywords | エンドミル / 難削材 / データマイニング / クラスタリング |
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| Outline of Final Research Achievements |
The data-mining methods using hierarchical and non-hierarchical clustering methods to help engineers decide appropriate end-milling conditions were proposed in this study. The aim of our research is to construct a system that uses clustering techniques and tool catalog data to support the decision of end-milling conditions for difficult-to-cut materials. We used the K-means method and variable cluster analysis to find tool shape parameters that had a significant relationship with the end-milling conditions listed in the catalog. We used both the principal component analysis and the response surface method to derive end-milling condition by suing significant tool shape parameters obtained by clustering. Milling experiments using a square end mill under two sets of end-milling conditions for difficult-to-cut materials showed that catalog mining can be used to derive guidelines for deciding end-milling conditions.
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| Free Research Field |
工学
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