Machining is one of the most important and widely used manufacturing processes. Due to
complexity and uncertainty of the machining processes, of late, soft computing techniques …

In recent years, several papers on machining processes have focused on the use of artificial
neural networks for modeling surface roughness. Even in such a specific niche of …

Fused deposition modelling is a proven technology for the fabrication of both aesthetic and
functional prototypes. The obtainable roughness is the most limiting aspect for its …

This work presents a study on the applicability of radial base function (RBF) neural networks
for prediction of Roughness Average (Ra) in the turning process of SAE 52100 hardened …

Surface roughness of the workpiece is an important parameter in machining technology.
Wiper inserts have emerged as a significantly class of cutting tools, which are increasingly …

In the present work, two different types of artificial neural network (ANN) architectures viz.
back propagation neural network (BPNN) and radial basis function network (RBFN) have …

In materials science, performance prediction of materials plays an important role in
improving the quality of materials as well as preventing serious damage to the environment …

Metal cutting fluids change performance of machining operations because of their
lubrication, cooling, and chip flushing functions. But the use of cutting fluid has become more …

Temper-grade aluminum alloy Al-6061-T6 is commonly used for many engineering
purposes owing to its superior mechanical properties. Due to the practical importance …

In the metal cutting process of machine tools, the quality of the surface roughness of the
product is very important to improve the friction performance, corrosion resistance, and …