Abstract In this new technological world, CNC and manual turning operations engage in a significant role different types of designing manufacturing industries. Before initiating the processes, analysis is crucial part process. This study involves modelling machining process cylindrical AA6082-T6 workpiece with Tungsten Carbide tip tool. A 3D model first modelled on CATIA V5 then carried Ansys R...

Product surface quality material removal rate play a great role in the current manufacturing industry. The use of artificial intelligence becomes immensely important component research work. . In today advanced technology era, CNC lathe is common and essential to enhance productivity this work, application neural network has been shown predict values finish MRR during turning operation on machi...

The purpose of this study is mainly to develop an information and communication technology (ICT)-based intelligent dimension inspection and tool wear compensation method for precision tuning. With the use of vibration signal processing/characteristics analysis technology combined with ICT, statistical analysis, and diagnosis algorithms, the method can be used to proceed with an on-line dimensio...

The aim of this research is to investigate the optimization of cutting parameters (cutting speed, feed rate and depth of cut) for surface roughness and metal removal rate in turning of AISI 8620 steel using coated carbide insert. Experiments have been carried out based on Taguchi L9 standard orthogonal array design with three process parameters namely cutting speed, feed rate and depth of cut f...

This study presents a new method for modeling an adaptive neuro-fuzzy inference system (ANFIS) based on vibration for predicting surface roughness in the CNC turning process. The input parameters of the model are insert nose radius, cutting speed, feed rate, depth of cut and vibration amplitude, which determine the output parameter of the surface roughness. A Gauss type membership function was ...