Machined surface profile and roughness are important parameters in evaluating the quality of a machining operation. They are resulted from the transformation of the complex tool-workpiece displacements involving the dynamics of the machine tool mechanical system, cutting process, and cutting motions. The focus of this study is the fundamental understanding of the surface profile formation during turning and development of regression and neural network (NN) models of surface roughness incorporating the effects of cutting parameters and tool-workpiece displacements. Also, a bifurcated opto- electrical transducer was developed for on-line monitoring of surface roughness based on the scattering of laser beams from machined surface. The feasibil...
This proposed work deals with the development of surface roughness prediction model for turning of A...
AbstractPrediction of surface roughness is always considered important in the manufacturing field. A...
In this study, models based on artificial neural networks (ANN) and regression analysis were develop...
This work studies the feasibility of on-line monitoring of surface roughness in turning operations u...
Quality of surface roughness has a great impact on machine parts during their useful life. The machi...
In recent years a direct method of surface finish quality detection by electrical resistance, optic...
For defining surface finish and monitoring tool wear is essential for optimisation of machining para...
Surface roughness, an indicator of surface quality, is one of the most specified customer requiremen...
In this study, a milling system based on the in-line surface roughness measurement during machining ...
In this present work, the important challenge is to manufacture high quality and low cost products w...
The aim of this study is to predict surface roughness in end milling of AISI 1040 steel. In realisin...
Surface roughness and cutting forces are considered as important factors to determine machinability ...
A neural network modeling approach is presented for the prediction of surface texture parameters dur...
Artificial Neural Network is a powerful tool for prediction of parameter values, which presents a se...
In the metal cutting process of machine tools, the quality of the surface roughness of the product i...
This proposed work deals with the development of surface roughness prediction model for turning of A...
AbstractPrediction of surface roughness is always considered important in the manufacturing field. A...
In this study, models based on artificial neural networks (ANN) and regression analysis were develop...
This work studies the feasibility of on-line monitoring of surface roughness in turning operations u...
Quality of surface roughness has a great impact on machine parts during their useful life. The machi...
In recent years a direct method of surface finish quality detection by electrical resistance, optic...
For defining surface finish and monitoring tool wear is essential for optimisation of machining para...
Surface roughness, an indicator of surface quality, is one of the most specified customer requiremen...
In this study, a milling system based on the in-line surface roughness measurement during machining ...
In this present work, the important challenge is to manufacture high quality and low cost products w...
The aim of this study is to predict surface roughness in end milling of AISI 1040 steel. In realisin...
Surface roughness and cutting forces are considered as important factors to determine machinability ...
A neural network modeling approach is presented for the prediction of surface texture parameters dur...
Artificial Neural Network is a powerful tool for prediction of parameter values, which presents a se...
In the metal cutting process of machine tools, the quality of the surface roughness of the product i...
This proposed work deals with the development of surface roughness prediction model for turning of A...
AbstractPrediction of surface roughness is always considered important in the manufacturing field. A...
In this study, models based on artificial neural networks (ANN) and regression analysis were develop...