Autonomous optimization of cutting conditions in end milling operation based on deep reinforcement learning (Offline training in simulation environment for feed rate optimization)
Full automation of manufacturing is strongly desired to improve the productivity. Autonomous optimization of the cutting conditions in the end milling operation is one of the challenges in achieving this goal. This paper proposes a system for optimization of the cutting conditions based on Deep Q-Ne...
Main Authors: | Kazuki KANEKO, Toshihiro KOMATSU, Libo ZHOU, Teppei ONUKI, Hirotaka OJIMA, Jun SHIMIZU |
---|---|
Format: | Article |
Language: | English |
Published: |
The Japan Society of Mechanical Engineers
2023-09-01
|
Series: | Journal of Advanced Mechanical Design, Systems, and Manufacturing |
Subjects: | |
Online Access: | https://www.jstage.jst.go.jp/article/jamdsm/17/5/17_2023jamdsm0064/_pdf/-char/en |
Similar Items
-
Dynamic Characteristics in The Cutting Operations with Small Diameter End Mills
by: Takashi MATSUMURA, et al.
Published: (2008-07-01) -
Cutting Forces Prediction in Ball End Milling
by: Hussain S. Kitan, et al.
Published: (2011-06-01) -
Cutting Forces Simulation for End Milling
by: Petrakov Y. V., et al.
Published: (2023-10-01) -
An Experimental Investigation on Micro End Milling with High-Speed Up Cut Milling for Hardened Die Steel
by: Haruki Kino, et al.
Published: (2020-10-01) -
Tool wear mechanism in up-cut end milling of AISI 1050 at different feed rates
by: Ryutaro TANAKA, et al.
Published: (2020-03-01)