Multi-objective Optimization of Cutting Parameters for Machining Process of Ni-Rich NiTiHf High-Temperature Shape Memory Alloy Using Genetic Algorithm

This study focuses on optimizing cutting parameters of NiTiHf high-temperature shape memory alloys using a multi-objective optimization method. The empirical models are used to predict outputs in a turning process of Ni-rich NiTiHf and compared to experimental data. Cutting parameters, such as cutti...

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Veröffentlicht in:Shape memory and superelasticity : advances in science and technology 2021, Vol.7 (2), p.270-279
Hauptverfasser: Kabil, A. O., Kaynak, Y., Saruhan, H., Benafan, O.
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Sprache:eng
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Zusammenfassung:This study focuses on optimizing cutting parameters of NiTiHf high-temperature shape memory alloys using a multi-objective optimization method. The empirical models are used to predict outputs in a turning process of Ni-rich NiTiHf and compared to experimental data. Cutting parameters, such as cutting speed, feed rate, and depth of cut, have found a great effect on performance criteria of turning processes in machining process of this alloy. These parameters were optimized by using Genetic Algorithm to obtain maximum tool life, minimum energy consumption, and maximum surface quality.
ISSN:2199-384X
2199-3858
DOI:10.1007/s40830-021-00328-z