Optimization of machining parameters to minimize surface roughness using integrated ANN-GA approach
The surface roughness is a widely used index of product quality in terms of precision fit of
mating surfaces, fatigue life improvement, corrosion resistance, aesthetics, etc. Surface …
mating surfaces, fatigue life improvement, corrosion resistance, aesthetics, etc. Surface …
[HTML][HTML] Analysis of fused filament fabrication parameters for sliding wear performance of carbon reinforced polyamide composite material fabricated parts using a …
Carbon-reinforced nylon composite material (PA12CF20), ie, polyamide, has been widely
used in the automotive, medical, and electronics industries for fabricating functional parts …
used in the automotive, medical, and electronics industries for fabricating functional parts …
Optimization of 3D printing process parameters to minimize surface roughness with hybrid artificial neural network model and particle swarm algorithm
M Shirmohammadi, SJ Goushchi… - Progress in Additive …, 2021 - Springer
Due to the significant impact on the product quality and performance, the surface roughness
of produced parts by 3D printers is one of the important factors in the 3D printing process …
of produced parts by 3D printers is one of the important factors in the 3D printing process …
Hot machining of difficult-to-cut materials: a review
Hot machining is a thermally-assisted metal cutting process which is favourably exercised
when machining of difficult-to-cut materials. In general, difficult-to-cut materials are …
when machining of difficult-to-cut materials. In general, difficult-to-cut materials are …
Modeling and prediction of surface roughness at the drilling of SLM-Ti6Al4V parts manufactured with pre-hole with optimized ANN and ANFIS
In this study, modeling of the surface roughness (Ra) with artificial neural networks (ANN) in
drilling the desired diameter of Ti6Al4V alloy produced by Selective Laser Melting (SLM) …
drilling the desired diameter of Ti6Al4V alloy produced by Selective Laser Melting (SLM) …
Investigation of the performance of the MQL, dry, and wet turning by response surface methodology (RSM) and artificial neural network (ANN)
In this approach, response surface methodology (RSM) and artificial neural network (ANN)
techniques were used in order to search for optimal prediction of uncontrollable machining …
techniques were used in order to search for optimal prediction of uncontrollable machining …
Response surface methodology and artificial neural network-based models for predicting performance of wire electrical discharge machining of inconel 718 alloy
V Lalwani, P Sharma, CI Pruncu… - Journal of Manufacturing …, 2020 - mdpi.com
This paper deals with the development and comparison of prediction models established
using response surface methodology (RSM) and artificial neural network (ANN) for a wire …
using response surface methodology (RSM) and artificial neural network (ANN) for a wire …
Surface characterization and specific wear rate prediction of r-GO/AZ31 composite under dry sliding wear condition
The effect of reduced graphene oxide (r-GO) nanosheets on the dry sliding wear behaviour
of AZ31 alloy composites produced by solvent based powder metallurgy technique has …
of AZ31 alloy composites produced by solvent based powder metallurgy technique has …
Parameter optimization of machining processes using a new optimization algorithm
R Venkata Rao, VD Kalyankar - Materials and Manufacturing …, 2012 - Taylor & Francis
A new advanced algorithm is proposed for the process parameter optimization of machining
processes. This algorithm is inspired by the teaching-learning process, and it works on the …
processes. This algorithm is inspired by the teaching-learning process, and it works on the …
ANN-GA based parametric optimization of Al-TiB2 metal matrix composite material processing technique
Over the years, aluminum metal matrix composites (AMMCs) have transitioned into a viable
replacement for traditional metals due to their exceptional strength-to-density ratio, higher …
replacement for traditional metals due to their exceptional strength-to-density ratio, higher …