File Download

There are no files associated with this item.

  • Find it @ UNIST can give you direct access to the published full text of this article. (UNISTARs only)

Views & Downloads

Detailed Information

Cited time in webofscience Cited time in scopus
Metadata Downloads

CNCToolDQN: Deep Q-learning on the anomaly detection and remaining useful life estimation for tool monitoring

Author(s)
Kim, Yearm
Advisor
Lim, Chiehyeon
Issued Date
2023-02
URI
https://scholarworks.unist.ac.kr/handle/201301/73961 http://unist.dcollection.net/common/orgView/200000665646
Publisher
Ulsan National Institute of Science and Technology (UNIST)
Degree
Master
Major
Department of Industrial Engineering

qrcode

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.