scispace - formally typeset
D

D. Hanumantha Rao

Researcher at Maturi Venkata Subba Rao Engineering College

Publications -  11
Citations -  256

D. Hanumantha Rao is an academic researcher from Maturi Venkata Subba Rao Engineering College. The author has contributed to research in topics: Network model & Electrical discharge machining. The author has an hindex of 5, co-authored 11 publications receiving 233 citations.

Papers
More filters
Journal ArticleDOI

Development of hybrid model and optimization of surface roughness in electric discharge machining using artificial neural networks and genetic algorithm

TL;DR: In this article, the authors aimed at optimizing the surface roughness of die sinking electric discharge machining (EDM) by considering the simultaneous affect of various input parameters such as peak current and voltage.

Development of hybrid model and optimization of metal removal rate in electric discharge machining using artificial neural networks and genetic algorithm

TL;DR: In this paper, the authors aimed at optimizing the metal removal rate of die sinking electric discharge machining (EDM) by considering the simultaneous affect of various input parameters such as peak current and voltage.
Journal ArticleDOI

Evolution of Artificial Neural Network (ANN) model for predicting secondary dendrite arm spacing in aluminium alloy casting

TL;DR: In this article, an Artificial Neural Network (ANN) model was developed to predict the response variable for varied input process variables, such as pouring temperature, insulation on riser and chill volume heat capacity.
Journal Article

Optimized high speed turning on Inconel 718 using Taguchi method based Grey relational analysis

TL;DR: In this article, the authors presented an optimum process parameters (speed, feed and depth of cut) to minimize the cutting force, surface roughness and tool flank wear together in CNC high speed dry turning of Inconel 718 using Taguchi method based Grey relational analysis.
Journal ArticleDOI

Mould Filling Ability Characterisation of Cast Aluminium Alloys Using Design of Experiments

TL;DR: In this paper, the mould filling ability of aluminium alloys LM6 and LM25 has been studied in the case of complex-shaped castings where section thickness is varying considerably, and the results from experimentation are analyzed to find the influence of the process parameters on mold filling ability.