Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Suiyan Shang"'
Publikováno v:
Digital Twin, Vol 3 (2024)
Background The quality of machined parts is considered as a relevant factor to evaluate the production performance of machine tools. For mapping the production performance into a digital twin machine tool, a virtual metrology model for surface roughn
Externí odkaz:
https://doaj.org/article/eedf4e2f33a04c459da813ec76de07ce
Publikováno v:
Micromachines, Vol 14, Iss 11, p 2016 (2023)
This paper pioneers the use of the extreme learning machine (ELM) approach for surface roughness prediction in ultra-precision milling, leveraging the excellent fitting ability with small datasets and the fast learning speed of the extreme learning m
Externí odkaz:
https://doaj.org/article/6acddb3af60647b7959dac990e7ba2e3
Publikováno v:
Digital Twin, Vol 3 (2023)
Background: The quality of machined parts is considered as a relevant factor to evaluate the production performance of machine tools. For mapping the production performance into a digital twin machine tool, a virtual metrology model for surface rough
Externí odkaz:
https://doaj.org/article/e2b7bcd8ee024ec988ee0b90535dcf41
Publikováno v:
Mathematical Problems in Engineering, Vol 2020 (2020)
The prediction model is the most important part of the virtual metrology system. Predicting the performance of the machining process has been widely applied in manufacturing, which can reduce costs and improve efficiency compared with the manual oper
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0444b121eacb9676a49ef3fdf4b65bc6
https://doi.org/10.1155/2020/5740362
https://doi.org/10.1155/2020/5740362
Publikováno v:
Journal of the American Ceramic Society. 102:7564-7574
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b7043c6726ab83cf4aaa7c105da28502
https://doi.org/10.1111/jace.16651
https://doi.org/10.1111/jace.16651