In recent decades, the use of artificial intelligence (AI) techniques in the field of materials
modeling has received significant attention owing to their excellent ability to analyze a vast …

Global competition and rapidly changing customer requirements are demanding increasing
changes in manufacturing environments. Enterprises are required to constantly redesign …

In this study, a neural network approach is presented for the prediction and control of surface
roughness in a computer numerically controlled (CNC) lathe. Experiments have been …

An artificial neural network (ANN) model was developed for the analysis and prediction of
the relationship between cutting and process parameters during high-speed turning of nickel …

Metal cutting mechanics is quite complicated and it is very difficult to develop a
comprehensive model which involves all cutting parameters affecting machining variables …

In today's accelerating world economy, the drive to continually cut costs and focus on core
competencies has driven many to outsource some or all of their production. In this …

This paper aims at presenting the effective parameters on surface roughness in machining
process. Many investigations have been carried out on the offline or online machining …

In manufacture sector, the surface finish quality has considerable importance that can affect
the functioning of a component, and possibly its cost. The surface quality is an significant …

This paper presents a system for automated, non-contact, and flexible prediction of surface
roughness of end-milled parts through a machine vision system which is integrated with an …

Surface quality is one of the most impellent customer requirements in machining. The main
aspect of surface quality on machined parts is probably surface integrity, such as roughness …