Predictive Modeling of Surface Roughness and Feed Force in Al-50wt% Si Alloy Milling Based on Response Surface Method and Various Optimal Algorithms

Al-50wt% Si alloy is considered as a difficult-to-machine material and is lack of precision machining research. In this paper, the response surface methodology (RSM), artificial neural network (ANN) and genetic algorithm (GA) are coupled to determine the optimum cutting conditions leading to the min...

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Veröffentlicht in:	Arabian journal for science and engineering (2011) 2023-03, Vol.48 (3), p.3209-3225
Hauptverfasser:	Jing, Lu, Niu, Qiulin, Zhan, Dilei, Li, Shujian, Yue, Wenhui
Format:	Artikel
Sprache:	eng
Schlagworte:	Aluminum base alloys Artificial neural networks Axial forces Cutting parameters Cutting speed Engineering Entropy (statistics) Genetic algorithms Humanities and Social Sciences Mathematical models Milling (machining) multidisciplinary Multiple objective analysis Optimization Precision machining Prediction models Process parameters Research Article-Mechanical Engineering Response surface methodology Science Silicon base alloys Surface roughness Variance analysis Weighting methods
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