Investigation of the performance of the MQL, dry, and wet turning by response surface methodology (RSM) and artificial neural network (ANN)
- DOI
- 10.1007/s00170-017-0589-2
- Published
- 2017-07-04
- Container
- The International Journal of Advanced Manufacturing Technology
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1007/s00170-017-0589-2,
title = {Investigation of the performance of the MQL, dry, and wet turning by response surface methodology (RSM) and artificial neural network (ANN)},
author = {Mourad Nouioua and Mohamed Athmane Yallese and Riad Khettabi and Salim Belhadi and Mohamed Lamine Bouhalais and François Girardin},
year = {2017},
journal = {The International Journal of Advanced Manufacturing Technology},
doi = {10.1007/s00170-017-0589-2},
url = {https://doi.org/10.1007/s00170-017-0589-2}
}RIS
TY - JOUR TI - Investigation of the performance of the MQL, dry, and wet turning by response surface methodology (RSM) and artificial neural network (ANN) AU - Mourad Nouioua AU - Mohamed Athmane Yallese AU - Riad Khettabi AU - Salim Belhadi AU - Mohamed Lamine Bouhalais AU - François Girardin PY - 2017 JO - The International Journal of Advanced Manufacturing Technology DO - 10.1007/s00170-017-0589-2 UR - https://doi.org/10.1007/s00170-017-0589-2 ER -
APA
Nouioua, M., Yallese, M. A., Khettabi, R., Belhadi, S., Bouhalais, M. L., & Girardin, F. (2017). Investigation of the performance of the MQL, dry, and wet turning by response surface methodology (RSM) and artificial neural network (ANN). The International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-017-0589-2
Source records
- crossref · retrieved 2026-11-10T09:07:47.335Z