dc.citation.endPage |
157 |
- |
dc.citation.startPage |
133 |
- |
dc.citation.title |
JOURNAL OF MANUFACTURING SYSTEMS |
- |
dc.citation.volume |
76 |
- |
dc.contributor.author |
Kim, Gyeongho |
- |
dc.contributor.author |
Yang, Sang Min |
- |
dc.contributor.author |
Kim, Dong Min |
- |
dc.contributor.author |
Choi, Jae Gyeong |
- |
dc.contributor.author |
Lim, Sunghoon |
- |
dc.contributor.author |
Park, Hyung Wook |
- |
dc.date.accessioned |
2024-08-08T11:35:05Z |
- |
dc.date.available |
2024-08-08T11:35:05Z |
- |
dc.date.created |
2024-08-07 |
- |
dc.date.issued |
2024-10 |
- |
dc.identifier.bibliographicCitation |
JOURNAL OF MANUFACTURING SYSTEMS, v.76, pp.133 - 157 |
- |
dc.identifier.doi |
10.1016/j.jmsy.2024.07.010 |
- |
dc.identifier.issn |
0278-6125 |
- |
dc.identifier.scopusid |
2-s2.0-85199874999 |
- |
dc.identifier.uri |
https://scholarworks.unist.ac.kr/handle/201301/83419 |
- |
dc.language |
영어 |
- |
dc.publisher |
Elsevier BV |
- |
dc.title |
Developing a deep learning-based uncertainty-aware tool wear prediction method using smartphone sensors for the turning process of Ti-6Al-4V |
- |
dc.type |
Article |
- |
dc.description.isOpenAccess |
FALSE |
- |
dc.type.docType |
Article |
- |
dc.description.journalRegisteredClass |
scie |
- |
dc.description.journalRegisteredClass |
scopus |
- |