2024
DOI: 10.1155/2024/9129669
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Predictive Modeling of Tool Life in Turning Using ANN‐Taguchi Hybridization

Shrishail Sollapur B.,
Shubham R. Suryawanshi,
Mitali Mhatre S.
et al.

Abstract: 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 tool’s material, and those of the workpiece being machined. Understanding precisely how each of these factors impacts tool life is essential for refining processes and choosing the right tool. There are established… Show more

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