An application of hybrid Taguchi-ANN to predict tool wear for turning EN24 material
This work is an attempt to predict tool wear for turning EN24 material by the hybrid Taguchi-ANN (Taguchi-Artificial Neural Network) method. The objective is to minimize the tool wear. The independent factors are cutting environment, feed rate, depth of cut, nose radius, and tool type. A Spinner num...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2024-01-01
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| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0186432 |