K. Leo Dev Wins

TL;DR: In this paper, an attempt was made to develop a model based on Artificial Neural Network to simulate hard turning of AISI H13 steel with minimal cutting fluid application, which is expected to predict the surface roughness in terms of cutting parameters.

TL;DR: In this paper, two distinct and novel types of aluminium hybrid composites and characterize their mechanical properties and microstructure were introduced and the composite material was processed through the melt-stir casting method and characterized by analyzing their densities, micro hardness, Charpy impact strength, tensile strength and peak elongation.

TL;DR: This review summarizes the vital findings in AFSD with particular emphasis on microstructure evolution and physical properties and suggested strategies for the widespread adoption of AFSD are suggested.

TL;DR: In this paper, a mixed mode solar dryer of forced convection type, integrated with a CuO nanoparticle coated flat plate solar collector was developed and its effectiveness of drying maize under the meteorological conditions of Coimbatore, India was evaluated.

TL;DR: In this paper, the authors proposed a hybrid genetic algorithm and ANN model for the prediction of surface roughness in a cylindrical grinding machine with Silicon Carbide grinding wheel, and the results show the feasibility of the proposed method in the predictive modeling and optimization of grinding parameters.