IPASJ INTERNATIONAL JOURNAL OF COMPUTER SCIENCE(IIJCS)

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ISSN 2321-5992

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EXPERIMENTAL INVESTIGATION OF OPTIMAL MACHINING PARAMETERS OF MILD STEEL IN CNC MILLING USING PARTICLE SWARM OPTIMIZATION, Authors : N.V.MAHESH BABU TALUPULA, NERSU RADHIKA,IPASJ INTERNATIONAL JOURNAL OF COMPUTER SCIENCE(IIJCS) ,http://www.ipasj.org/IIJCS/IIJCS.htm

Volume & Issue no: Volume 3, Issue 1, January 2015


Title:
EXPERIMENTAL INVESTIGATION OF OPTIMAL MACHINING PARAMETERS OF MILD STEEL IN CNC MILLING USING PARTICLE SWARM OPTIMIZATION
Author Name:
N.V.MAHESH BABU TALUPULA, NERSU RADHIKA
Abstract:
ABSTRACT Computer Numerical Control (CNC) machines are widely used in manufacturing industry. Traditional machines such as vertical millers, centre lathes, shaping machines, routers etc.... operated by a trained engineer have, in many cases, been replaced by computer control machines. Since the dawn of the CNC (Computer Numerical Control) machines introduction in the machining sector, they have been praised for being accurate, fast, consistent and flexible. Although CNC machines are not totally independent, a lot of major industries depend on these wonder machines. Common CNC-dependent industries include the metal industry and the woodworking industry. Productivity as well as quality both has a similar impact on final product. In this research work, milling experiments are carried out on Mild Steel. Full factorial experimentation is adapted for conducting pilot experiments to study the effects of cutting parameters on machining time and roughness. Empirical relations for surface roughness have been developed for the proposed Mild Steel material based on pilot experiments. Then, Particle Swarm Optimization (PSO) technique was implemented for predicting optimum cutting parameters for any desired roughness in minimum machining time. Most of the research work ends up here without validating the optimal cutting parameters. However, most importantly, in this research work, validation experiments are conducted as per the optimized parameters obtained by PSO. The predicted values of machining time and roughness obtained by PSO are compared with experimental results. It is found that the predicted values are in good agreement with the measured machining time and roughness. The findings of the present work infer that the use of the proposed methodology can greatly replace the laborious process of selection of cutting parameters by trial and error method. This will reduce the wastage of resources used for manufacturing. Due to this, production cost and selling cost of the component can be reduced; hence sales and profit for the industries can be improved to a great extent. Keywords: -Optimization, Particle Swarm Optimization, CNC milling parameters, surface finish, machining time.
Cite this article:
N.V.MAHESH BABU TALUPULA, NERSU RADHIKA , " EXPERIMENTAL INVESTIGATION OF OPTIMAL MACHINING PARAMETERS OF MILD STEEL IN CNC MILLING USING PARTICLE SWARM OPTIMIZATION " , IPASJ INTERNATIONAL JOURNAL OF COMPUTER SCIENCE(IIJCS), Volume 3, Issue 1, January 2015 , pp. 013-028 , ISSN 2321-5992.
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