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Coupling Taguchi experimental designs with deep adaptive learning enhanced AI process models for experimental cost savings in manufacturing process development

Abstract The Aluminum alloy AA7075 workpiece material is observed under dry finishing turning operation. This work is an investigation reporting promising potential of deep adaptive learning enhanced artificial intelligence process models for L18 (6133) Taguchi orthogonal array experiments and major...

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Principais autores: Syed Wasim Hassan Zubair, Syed Muhammad Arafat, Sarmad Ali Khan, Sajawal Gul Niazi, Muhammad Rehan, Muhammad Usama Arshad, Nasir Hayat, Tauseef Aized, Ghulam Moeen Uddin, Fahid Riaz
Format: Artigo
Sprog:Inglês
Udgivet: Nature Portfolio 2024-10-01
Serier:Scientific Reports
Fag:
Artificial Intelligence
Taguchi
Dry Finishing
Turning
Aerospace Alloy
Neural networks
Online adgang:https://doi.org/10.1038/s41598-024-73669-1
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