The machine learning (ML) approach, motivated by artificial intelligence (AI), is an inspiring
mathematical algorithm that accurately simulates many engineering processes. Machine …

In tribology, a considerable number of computational and experimental approaches to
understand the interfacial characteristics of material surfaces in motion and tribological …

Aluminum Metal Matrix Composites (MMCs) sought over other conventional materials in the
field of aerospace, automotive and marine applications owing to their excellent improved …

The artificial neural network (ANN) approach motivated by the biological nervous system is
an inspiring mathematical tool that simulates many complicated engineering applications …

This paper investigates the manufacturing of aluminium–boron carbide composites using
the stir casting method. Mechanical and physical properties tests to obtain hardness …

The coefficient of friction (CoF) obtained from tribological tests conducted on textured and
porous surfaces was analysed using the machine learning Radial Basis Function (RBF) …

The present paper discussed the development of a reliable and robust artificial neural
network (ANN) capable of predicting the tribological performance of three highly alloyed tool …

This paper deals with the fabrication of reduced graphene oxide (r-GO) reinforced
Magnesium Metal Matrix Composite (MMC) through a novel solvent based powder …

In the present study, wear and friction behaviour of Magnesium (Mg) Metal Matrix Composite
(MMC) reinforced with Silicon carbide (SiC) doped reduced graphene oxide (r-GO) …

In the present investigation, A390/graphite and A390/Al 2 O 3 surface composite (SC) layers
were fabricated using friction stir processing (FSP). The effect of tool rotational and traverse …