Surface roughness prediction models using artificial neural network (ANN) are developed to
investigate the effects of cutting conditions during turning of free machining steel …

This study presents a prediction method of surface roughness values for dry and cryogenic
turning of AISI 304 stainless steel using the ANFIS-QPSO machine learning approach …

Τhis chapter is aimed at providing current knowledge on the association of surface texture
with machining, along with recent advances in surface characterization and evaluation …

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 …

The present paper is aimed at studying the impact of cutting conditions on surface
roughness in turning of polyethertherketone (PEEK) composites. The latter are widely used …

The reliable characterization of surface topographies—especially in case of tribological
processes—requires complex and comprehensive solution methods. The use of a …

Although the effects of hard turning on surface integrity have been extensively studied over
the past decades, the fatigue behavior of hard turned ultra-high strength steels is still not …

The present paper investigates the influence of main cutting parameters on the machinability
during turning process for three typical materials namely AISI D6 tool steel, Ti6Al4V ELI and …

The study of machining nickel-based superalloys has assisted in developing new
techniques associated with cutting processes and tools. Hastelloy® X offers ideal properties …

Machinability of engineering materials is crucial for industrial manufacturing processes since
it affects all the essential aspects involved, eg workload, resources, surface integrity and part …