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Prediction of Extrusion Machine Stem Fatigue Life Using Structural and Fatigue Analysis.
Kim, Dong-Yul; Kim, Ji-Wook; Ha, Jin-Su; Jo, A-Ra; Lee, Sung-Yun; Jeong, Myeong-Sik; Ko, Dae-Cheol; Jang, Jin-Seok.
Afiliación
  • Kim DY; Gyeongbuk Research Institute of Vehicle Embedded Technology, Yeongcheon-si 38822, Republic of Korea.
  • Kim JW; Smart Manufacturing Technology R&D Group, Korea Institute of Industrial Technology, Daegu 42994, Republic of Korea.
  • Ha JS; Smart Manufacturing Technology R&D Group, Korea Institute of Industrial Technology, Daegu 42994, Republic of Korea.
  • Jo AR; Smart Manufacturing Technology R&D Group, Korea Institute of Industrial Technology, Daegu 42994, Republic of Korea.
  • Lee SY; Smart Manufacturing Technology R&D Group, Korea Institute of Industrial Technology, Daegu 42994, Republic of Korea.
  • Jeong MS; Smart Manufacturing Technology R&D Group, Korea Institute of Industrial Technology, Daegu 42994, Republic of Korea.
  • Ko DC; Department of Nanomechatronics Engineering, Pusan National University, Pusan 46241, Republic of Korea.
  • Jang JS; Smart Manufacturing Technology R&D Group, Korea Institute of Industrial Technology, Daegu 42994, Republic of Korea.
Materials (Basel) ; 16(8)2023 Apr 18.
Article en En | MEDLINE | ID: mdl-37110028
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Materials (Basel) Año: 2023 Tipo del documento: Article Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Materials (Basel) Año: 2023 Tipo del documento: Article Pais de publicación: Suiza