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Magdy M. El Rayes

Researcher at King Saud University

Publications -  27
Citations -  383

Magdy M. El Rayes is an academic researcher from King Saud University. The author has contributed to research in topics: Surface roughness & Machining. The author has an hindex of 9, co-authored 22 publications receiving 231 citations.

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ANN Surface Roughness Optimization of AZ61 Magnesium Alloy Finish Turning: Minimum Machining Times at Prime Machining Costs

TL;DR: A novel Edgeworth–Pareto optimization of an artificial neural network (ANN) is presented in this paper for surface roughness (Ra) prediction of one component in computer numerical control (CNC) turning over minimal machining time (Tm) and at prime machining costs (C).
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Investigations of surface quality and energy consumption associated with costs and material removal rate during face milling of AISI 1045 steel

TL;DR: In this article, a multilayer regression analysis was conducted on obtained experimental results and inducing non-linear mathematical equations with high coefficient of determination (R2 = 0.98).
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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 Сhips

TL;DR: In this paper, the effects of both the modern method of hardening AA6061 shafts and the finish turning conditions on surface roughness, Ra, and the minimum machining time for unit-volume removal, Tm, while also establishing the cost price of processing one part, C.
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Optimization of cutting conditions using artificial neural networks and the Edgeworth-Pareto method for CNC face-milling operations on high-strength grade-H steel

TL;DR: An unprecedented Pareto frontier for Ra and Tm was obtained for the finished grade-H steel workpiece using an ANN algorithm that was then used to determine optimized cutting conditions.
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Towards Optimization of Machining Performance and Sustainability Aspects when Turning AISI 1045 Steel under Different Cooling and Lubrication Strategies

TL;DR: An extensive analysis has been presented and discussed to study the effectiveness of using different cooling and lubrication techniques when turning AISI 1045 steel, and MQL-nanofluid offered promising results.