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An improved surface roughness prediction model using Box-Cox transformation with RSM in end milling of EN 353

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Abstract

In the present work, an attempt has been made to use Box-Cox transformation with response surface methodology to develop improve surface roughness prediction model in end milling of EN 353 steel using carbide inserts. The analysis has been carried out in two stages. In the first stage quadratic model has been developed in terms of feed, speed, depth of cut and nose radius using response surface methodology (RSM) based on center composite rotatable design (CCRD). The quadratic model, thus developed predicts the surface roughness with 92% accuracy. In the second stage, the improved quadratic model has been developed using Box-Cox transformation with RSM based on CCRD. The prediction ability of this develop model has been found more accurate (mean absolute error 4.7%) than previous one. An attempt has also been made to investigate the influence of cutting parameters on surface roughness. The result shows that the machining speed is the main influencing factor on the surface roughness while the depth of cut has no significant influence.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Sant longowal Institute of Engineering & Technology, Longowal, 148 106, Pb, India

    Bhuvnesh Bhardwaj, Rajesh Kumar & Pradeep K. Singh

Authors
  1. Bhuvnesh Bhardwaj
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  2. Rajesh Kumar
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  3. Pradeep K. Singh
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Correspondence to Pradeep K. Singh.

Additional information

Recommended by Associate Editor Pradeep K. Singh

Bhuvnesh Bhardwaj received the Bachelor’s degree in Mechanical Engineering from Government Engineering College (GEC), Ajmer in 2001, and M. Tech. in Manufacturing Systems Engineering from Sant Longowal Institute of Engineering & Technology (SLIET), Longowal in 2006. He is currently pursuing the Ph.D. from Department of Mechanical Engineering at SLIET, Longowal on “Study of surface Roughness in Metal Machining”.

Rajesh Kumar is Professor in the Department of Mechanical Engineering at Sant Longowal Institute of Engineering & Technology, Longowal. He received his Doctoral degree from Indian Institute of Technology Delhi. Dr. Kumar has around 20-year of professional experience in teaching, industry and research. His research interests are in Metal Cutting, Fault diagnosis & Vibration analysis, and Optical & Opto-electronic Sensors applied to engineering measurements. Citation index (h-index) of his publications is 7.

Pradeep K. Singh is a Professor along with the responsibility of the Head, Department of Mechanical Engineering, at Sant Longowal Institute of Engineering & Technology, Longowal. He has also served in manufacturing industry at Encardio-rite Electronics (P) Ltd. Lucknow, and Scooters India Ltd. Lucknow for a small span of time. He received B. Tech. in Mechanical Engineering from the Institute of Engineering & Technology (IET), Lucknow, in 1990, M. Tech. in Mechanical Engineering (specialization in Production Engineering) from the Institute of Technology Banaras Hindu University (IT-BHU), Varanasi, in 1992, and Ph.D. in Mechanical Engineering from the Indian Institute of Technology (IIT), Roorkee, in 2005. Dr. Singh has more than 20-year of professional experience in teaching, industry and research. He has been a reviewer of several international journals, viz. IIE Transactions, Computers in Industry, Computer Aided Design, Proc. IMechE (Part B) Journal of Engineering Manufacture, Journal of Material Processing Technology, International Journal of Advanced Manufacturing Technology, Journal of Automation, Mobile Robotics & Intelligent Systems, Annals of Operations Research and Asian Journal of Scientific Research etc. He has been the guest editor to International Journal of Applied Engineering Research, 5(17), 2010, and International Journal of Engineering Studies, 2(3), 2010. His research interests include Tolerance Design, Design for Manufacture and Assembly, Metal Machining, Advanced Optimization of Mechanical Systems, and Modeling & Simulation of Mechanical Systems, etc.

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Bhardwaj, B., Kumar, R. & Singh, P.K. An improved surface roughness prediction model using Box-Cox transformation with RSM in end milling of EN 353. J Mech Sci Technol 28, 5149–5157 (2014). https://doi.org/10.1007/s12206-014-0837-4

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  • DOI: https://doi.org/10.1007/s12206-014-0837-4

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