このエントリーをはてなブックマークに追加
ID 68939
Title Alternative
Development of a guideline proposal system for correcting cutting conditions based on the overhang length of ball end-mills
FullText URL
fulltext.pdf 3.59 MB
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
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.
Keywords
Data mining
Cutting conditions
Machine learning
Random Forest Regression
Ball end-mill
Tool overhang length
Published Date
2025
Publication Title
Transactions of the JSME (in Japanese)
Volume
volume91
Issue
issue946
Publisher
日本機械学会
Start Page
24-00128
ISSN
2187-9761
Content Type
Journal Article
language
Japanese
OAI-PMH Set
岡山大学
Copyright Holders
© 2025 一般社団法人日本機械学会
File Version
publisher
DOI
Related Url
isVersionOf https://doi.org/10.1299/transjsme.24-00128
License
https://creativecommons.org/licenses/by-nc-nd/4.0/deed.ja