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Optimization of process parameters for surface roughness and tool wear in milling TC17 alloy using Taguchi with grey relational analysis
oleh: Zhe Wang, Lei Li
Format: | Article |
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Diterbitkan: | SAGE Publishing 2021-02-01 |
Deskripsi
To improve machining quality and processing efficiency, the Taguchi analysis method is employed to design the milling tests of titanium alloy TC17. According to results based on the signal-to-noise ratio method, the cutting depth plays a critical role in improving the surface roughness and tool wear. The grey correlation analysis is a multi-objective optimization method that can help to acquire process parameters combination of the optimal surface roughness and the optimal tool wear. Finally, the correctness of multi-objective optimization results is verified through comparison experiments. The research results can provide process guidance and data reference for the actual production processing.