Yanis, Muhammad and Mohruni, Amrifan Saladin and Sharif, Safian and Yani, Irsyadi (2019) OPTIMUM PERFORMANCE OF GREEN MACHINING ON THIN WALLED TI6AL4V USING RSM AND ANN IN TERMS OF CUTTING FORCE AND SURFACE ROUGHNESS. Jurnal Teknologi, 81 (6). pp. 51-60. ISSN 0127-9696
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Thin walled titanium alloys are mostly applied in the aerospace industry owing to their favorable characteristic such as high strength-to-weight ratio. Besides vibration, the friction at the cutting zone in milling of thin-walled Ti6Al4V will create inconsistencies in the cutting force and increase the surface roughness. Previous researchers reported the use of vegetable oils in machining metal as an effort towards green machining in reducing the undesirable cutting friction. Machining experiments were conducted under Minimum Quantity Lubrication (MQL) using coconut oil as cutting fluid, which has better oxidative stability than other vegetable oil. Uncoated carbide tools were used in this milling experiment. The influence of cutting speed, feed and depth of cut on cutting force and surface roughness were modeled using response surface methodology (RSM) and artificial neural network (ANN). Experimental machining results indicated that ANN model prediction was more accurate compared to the RSM model. The maximum cutting force and surface roughness values recorded are 14.89 N, and 0.161 µm under machining conditions of 125 m/min cutting speed, 0.04 mm/tooth feed, 0.25 mm radial depth of cut (DOC) and 5 mm axial DOC.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Optimization, green machining, thin-walled Ti6Al4V, RSM, ANN, cutting force, surface roughness |
| Subjects: | T Technology > TJ Mechanical engineering and machinery > TJ1125-1345 Machine shops and machine shop practice > TJ1180 Machining, Ceramic materials--Machining-Strength of materials-Machine tools-Design and construction > TJ1180.N595 Machining |
| Divisions: | 03-Faculty of Engineering > 21101-Mechanical Engineering (S2) |
| Depositing User: | Prof Amrifan Saladin Mohruni |
| Date Deposited: | 09 Dec 2019 02:27 |
| Last Modified: | 09 Dec 2019 02:27 |
| URI: | http://repository.unsri.ac.id/id/eprint/20515 |
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