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ANN Surface Roughness Optimization of AZ61 Magnesium Alloy Finish Turning: Minimum Machining Times at Prime Machining Costs
Faculty
Engineering
Year:
2018
Type of Publication:
ZU Hosted
Pages:
Authors:
Mohamed Adel Taha Mohamed Abass
Staff Zu Site
Abstract In Staff Site
Journal:
Materials mdpi
Volume:
Keywords :
, Surface Roughness Optimization , AZ61 Magnesium Alloy Finish
Abstract:
Magnesium alloys are widely used in aerospace vehicles and modern cars, due to their rapid machinability at high cutting speeds. A novel Edgeworth–Pareto optimization of an artificial neural network (ANN) is presented in this paper for su
Author Related Publications
Mohamed Adel Taha Mohamed Abass , "Artificial Intelligence Monitoring of Hardening Methods and Cutting Conditions and Their Effects on Surface Roughness, Performance, and Finish Turning Costs of Solid-State Recycled Aluminum Alloy 6061 Chips", mdpi, 2018
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Mohamed Adel Taha Mohamed Abass , "Effect of Equal Channel Angular Pressing on the Surface Roughness of Solid State Recycled Aluminum Alloy 6061 Chips", Hindawi, 2017
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Mohamed Adel Taha Mohamed Abass , "Effect of extrusion temperature on the surface roughness of solid state recycled aluminum alloy 6061 chips during turning operation", SAGE, 2017
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Mohamed Adel Taha Mohamed Abass , "Minimization of turning time for high-strength steel with a given surface roughness using the Edgeworth–Pareto optimization method", Springer, 2017
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Mohamed Adel Taha Mohamed Abass , "ANN Surface Roughness Optimization of AZ61 Magnesium Alloy Finish Turning: Minimum Machining Times at Prime Machining Costs", mdpi, 2018
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Mohammed Adly AttiaIbrahiem , "Nonlinear analysis of functionally graded nanoscale beams incorporating the surface energy and microstructure effects", Elsevier, 2017
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