%0 Journal Article
	%A Mangesh R. Phate and  V. H. Tatwawadi
	%D 2014
	%J International Journal of Mechanical and Mechatronics Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 85, 2014
	%T ANN Based Model Development for Material Removal Rate in Dry Turning in Indian Context
	%U https://publications.waset.org/pdf/9997427
	%V 85
	%X This paper is intended to develop an artificial neural network (ANN) based model of material removal rate (MRR) in the turning of ferrous and nonferrous material in a Indian small-scale industry. MRR of the formulated model was proved with the testing data and artificial neural network (ANN) model was developed for the analysis and prediction of the relationship between inputs and output parameters during the turning of ferrous and nonferrous materials. The input parameters of this model are operator, work-piece, cutting process, cutting tool, machine and the environment.

The ANN model consists of a three layered feedforward back propagation neural network. The network is trained with pairs of independent/dependent datasets generated when machining ferrous and nonferrous material. A very good performance of the neural network, in terms of contract with experimental data, was achieved. The model may be used for the testing and forecast of the complex relationship between dependent and the independent parameters in turning operations.

	%P 130 - 135