文献
J-GLOBAL ID:202102285471882228
整理番号:21A0578161
マイクロEDM掘削における工具摩耗と材料除去予測:データ駆動アプローチの利点【JST・京大機械翻訳】
Tool Wear and Material Removal Predictions in Micro-EDM Drilling: Advantages of Data-Driven Approaches
著者 (5件):
Bellotti Mattia
(Department of Mechanical Engineering, KU Leuven and Member Flanders Make, 3001 Leuven, Belgium)
,
Wu Ming
(Department of Mechanical Engineering, KU Leuven and Member Flanders Make, 3001 Leuven, Belgium)
,
Wu Ming
(School of Mechanical and Electrical Engineering, Guangdong University of Technology, Guangzhoug 510000, China)
,
Qian Jun
(Department of Mechanical Engineering, KU Leuven and Member Flanders Make, 3001 Leuven, Belgium)
,
Reynaerts Dominiek
(Department of Mechanical Engineering, KU Leuven and Member Flanders Make, 3001 Leuven, Belgium)
資料名:
Applied Sciences (Web)
(Applied Sciences (Web))
巻:
10
号:
18
ページ:
6357
発行年:
2020年
JST資料番号:
U7135A
ISSN:
2076-3417
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
スイス (CHE)
言語:
英語 (EN)