Please use this identifier to cite or link to this item:
http://nopr.niscpr.res.in/handle/123456789/4330| Title: | Metal cutting process parameters modeling: an artificial intelligence approach |
| Authors: | Tanikic, Dejan Manic, Miodrag Radenkovic, Goran Mancic, Dragan |
| Keywords: | Artificial neural networks;Metal cutting process;Neuro-fuzzy system |
| Issue Date: | Jun-2009 |
| Publisher: | CSIR |
| Abstract: | This study presents metal cutting process’ parameters modeling (cutting temperature, cutting force, and quality of machinedsurface) using artificial neural networks, and hybrid, adaptive neuro-fuzzy systems. Proposed models can be used for metalcutting process optimization, increasing productivity and reducing manufacturing costs. |
| Page(s): | 530-539 |
| ISSN: | 0022-4456 |
| Appears in Collections: | JSIR Vol.68(06) [June 2009] |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| JSIR 68(6) 530-539.pdf | 199.95 kB | Adobe PDF | View/Open |
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