ID | 68939 |
Title Alternative | Development of a guideline proposal system for correcting cutting conditions based on the overhang length of ball end-mills
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FullText URL | |
Author |
KODAMA, Hiroyuki
Faculty of Environmental, Life, Natural Science and Technology, Okayama University
Kaken ID
MORIYA, Yuki
Graduate school of Environmental, Life, Natural Science and Technology, Okayama University
MORIMOTO, Tatsuo
Graduate school of Environmental, Life, Natural Science and Technology, Okayama University
OHASHI, Kazuhito
Faculty of Environmental, Life, Natural Science and Technology, Okayama University
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Abstract | In the field of die and mold machining, determining appropriate cutting conditions is crucial. Factors such as tool geometry, machining path, work material characteristics, machining efficiency, and finishing accuracy must be taken into consideration. However, the current method of determining cutting conditions relies heavily on the intuition and experience of skilled engineers, and there is a need for a system to replace such knowledge. One of the critical factors affecting machining accuracy and efficiency is the tool overhang length, which is directly related to tool geometry. Unfortunately, there is no clear guideline for its determination. In a previous study, researchers developed a system to quickly derive cutting conditions using a data mining method and Random Forest Regression (RFR) applied to a tool catalog database. In this study, we constructed a new cutting condition compensation system based on the existing model, which accounts for the tool overhang length. The results of cutting experiments under high aspect ratio overhang lengths confirm that the correction coefficients proposed by the system are significant.
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Keywords | Data mining
Cutting conditions
Machine learning
Random Forest Regression
Ball end-mill
Tool overhang length
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Published Date | 2025
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Publication Title |
Transactions of the JSME (in Japanese)
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Volume | volume91
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Issue | issue946
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Publisher | 日本機械学会
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Start Page | 24-00128
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ISSN | 2187-9761
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Content Type |
Journal Article
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language |
Japanese
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OAI-PMH Set |
岡山大学
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Copyright Holders | © 2025 一般社団法人日本機械学会
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File Version | publisher
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DOI | |
Related Url | isVersionOf https://doi.org/10.1299/transjsme.24-00128
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License | https://creativecommons.org/licenses/by-nc-nd/4.0/deed.ja
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