Machinability study and multi-response optimization of cutting force, Surface roughness and tool wear on CNC turned Inconel 617 superalloy using Al2O3 Nanofluids in Coconut oil
| Autor: | R. Raghul, Arun Tom Mathew, Nouby M. Ghazaly, K. Venkatesan, S. Sanjith, S. Devendiran |
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| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Materials science Machinability Metallurgy 02 engineering and technology Industrial and Manufacturing Engineering Superalloy Taguchi methods 020303 mechanical engineering & transports 020901 industrial engineering & automation Lubricity 0203 mechanical engineering Machining Artificial Intelligence Surface roughness Tool wear Inconel |
| Zdroj: | Procedia Manufacturing. 30:396-403 |
| ISSN: | 2351-9789 |
| DOI: | 10.1016/j.promfg.2019.02.055 |
| Popis: | Inconel 617 alloy is corrosion and oxidation resistant, nickel-based alloy and emanates under tough to turn material. Moreover, turning off this alloy under MQL need attention. In this context, this work aims to examine the machinability study under MQL on CNC turning of 617 alloys by AlTiN PVD carbide cutting inserts. As a methodology, the Taguchi L9 orthogonal array parameter design and response surface optimization has been employed. 1D and 3D plots have been used to analysis on the collected machining data based on fitted regression model. The statistical analysis revealed % concentration impacted for force, cutting velocity influenced for surface roughness and tool wear. From the optimization analysis, 0.25% Al2O3 Nano-fluid in coconut oil along with a cutting speed of 40 m/min and 0.14 mm/rev feed rate. Abrasion, adhesion and diffusion wear are identified as wear mechanisms. The diameter of produced helical and tubular chips are different, and at high % concentration, the curl diameter is found to be increased due to the decrease in lubricity and increase tool friction on turning of Inconel 617. |
| Databáze: | OpenAIRE |
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