Predictive Modeling of Tool Life in Turning Using ANN-Taguchi Hybridization
A tool that will last is crucial for refining machining processes, influencing the quality of products, and reducing the expenses of making them. Previous research has demonstrated that several factors influence tool longevity, including the cutting depth, speed, the feed rate, the properties of the...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2024/9129669 |
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