Multi-objective optimization of surface roughness, cutting forces, productivity and Power consumption when turning of Inconel 718 - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue International Journal of Industrial Engineering Computations Année : 2016

Multi-objective optimization of surface roughness, cutting forces, productivity and Power consumption when turning of Inconel 718

Résumé

Nickel based super alloys are excellent for several applications and mainly in structural components submitted to high temperatures owing to their high strength to weight ratio, good corrosion resistance and metallurgical stability such as in cases of jet engine and gas turbine components. The current work presents the experimental investigations of the cutting parameters effects (cutting speed, depth of cut and feed rate) on the surface roughness, cutting force components, productivity and power consumption during dry conditions in straight turning using coated carbide tool. The mathematical models for output parameters have been developed using Box-Behnken design with 15 runs and Box-Cox transformation was used for improving normality. The results of the analysis have shown that the surface finish was statistically sensitive to the feed rate and cutting speed with the contribution of 43.58% and 23.85% respectively, while depth of cut had the greatest effect on the evolution of cutting force components with the contribution of 79.87% for feed force, 66.92% for radial force and 66.26% for tangential force. Multi-objective optimization procedure allowed minimizing roughness Ra, cutting forces and power consumption and maximizing material removal rate using desirability approach.

Dates et versions

hal-01999571 , version 1 (30-01-2019)

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Citer

Hamid Tebassi, Mohamed Athmane Yallese, Riad Khettabi, Salim Belhadi, Ikhlas Meddour, et al.. Multi-objective optimization of surface roughness, cutting forces, productivity and Power consumption when turning of Inconel 718. International Journal of Industrial Engineering Computations, 2016, pp.111-134. ⟨10.5267/j.ijiec.2015.7.003⟩. ⟨hal-01999571⟩
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