Development of surface roughness prediction model using 2 level full factorial design and to analyze during turning of AISI 1019 steel

Authors

  • Mr. Adesh Sharma1, Mr. Sanjay Singh2 1PG Research Scholar, 2Assistant Professor, Department of Mechanical Engineering, Jagannath University Chaksu, Jaipur Rajasthan

Abstract

Achieving the desired surface quality is of great importance for the functional behavior of the mechanical parts. Surface roughness is one of the important aspects of surface quality. It has an impact on the mechanical properties of the machined parts. The surface finish of the machined parts is greatly influenced by the cutting tool properties, machining parameters, work piece properties and cutting phenomenon. The proper selection of machining conditions can yield desired surface finish on the machined surface. So it can be achieved by establish empirical relationship between machining condition and surface roughness indicators using design of experiments (DOE). The proposed work will be employed for optimization of machining condition for minimum surface roughness and for maximum material removal rate in turning of AISI 52100 steel. A attempt has also been made to investigate the effect of turning parameters on surface roughness indicators and MRR using 2 level full factorial design. Key terms: DOE, feed, speed, surface roughness

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Published

2015-06-30

How to Cite

Mr. Sanjay Singh2, M. A. S. (2015). Development of surface roughness prediction model using 2 level full factorial design and to analyze during turning of AISI 1019 steel. International Journal of Engineering Technology and Computer Research, 3(3). Retrieved from https://www.ijetcr.org/index.php/ijetcr/article/view/205

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Articles