A Hybrid Approach for Predicting Critical Machining Conditions in Titanium Alloy Slot Milling Using Feature Selection and Binary Whale Optimization Algorithm

Monitoring the machining process is crucial for providing cost-effective, high-quality production and preventing unwanted accidents. This study aims to predict critical machining conditions related to surface roughness and tool breakage in titanium alloy slot milling. The Siemens SINUMERIK EDGE (SE)...

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Vydané v:	Machines (Basel) Ročník 11; číslo 8; s. 835
Hlavní autori:	Rahmani, Amirsajjad, Hojati, Faramarz, Hadad, Mohammadjafar, Azarhoushang, Bahman
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.08.2023
Predmet:	Algorithms Analysis Artificial intelligence binary whale optimization algorithm Cetacea feature selection Fourier transforms Machine tools Machining Machinists' tools Mathematical optimization milling Model testing Neural networks Optimization Sensors Slot milling Specialty metals industry Support vector machines Surface roughness Ti6Al4V Titanium alloys Titanium base alloys tool monitoring Workpieces
ISSN:	2075-1702, 2075-1702
On-line prístup:	Získať plný text
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