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I-Kaz methodology for predicting tool life of AlCrNCoated WCCo inserts in the machining of AISI 304 steel

This study proposes a real-time tool wear monitoring approach for dry milling of AISI 304 stainless steel using a Microflown PU sensor and the I-Kaz™ statistical feature. A Taguchi L18 orthogonal array was adopted to optimize cutting speed, feed rate, depth of cut and tool type (uncoated and AlCrN-c...

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Hauptverfasser: Mogana Priya Chinnasamy, Rajasekar Rathanasamy, Swetha R Kumar, Sathish Kumar Palaniappan
Format: Artigo
Sprache:Inglês
Veröffentlicht: Elsevier 2025-12-01
Schriftenreihe:MethodsX
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Online-Zugang:http://www.sciencedirect.com/science/article/pii/S2215016125005503
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