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
Journal: Veterinary Quarterly 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 , "ANN Surface Roughness Optimization of AZ61 Magnesium Alloy Finish Turning: Minimum Machining Times at Prime Machining Costs", mdpi, 2018 More
  • 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 More
  • 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 More
  • 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 More
  • 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 More

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