Volume 2, No. 3, July 2013

General Information

  • ISSN: 2278-0149 (Online)
  • Abbreviated Title:  Int. J. Mech. Eng. Robot. Res.  
  • Editor-in-Chief: ​Prof Richard (Chunhui) Yang, Western Sydney University, Australia
  • Associate Editor: Prof. B.V. Appa Rao, Andhra University; Prof. Ian R. McAndrew, Capitol Technology University, USA
  • Managing Editor: Murali Krishna. B
  • DOI: 10.18178/ijmerr
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International Journal of Mechanical Engineering and Robotics Research
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Optimization of Cutting Parameters of AlSI H13 with Multiple Performance Characteristics

Anmol Kumar and M K Paswan
Department of Mechanical Engg., National Institute of Technical Teachers’ Training and Research, Kolkata 700106, India.

Abstract—The selection of optimum process parameters plays a significant role to ensure quality of product. If more than one attribute comes into consideration it is very difficult to select the optimal setting which can achieve all quality requirements simultaneously. The present study response surface methodology is applied for optimization of process parameters for machining of hard material by CNC end milling. This study investigates the multi-response optimization of end milling process for an optimal parametric combination to yield the tool wear and surface roughness. It deals with the effects of three input process parameters chosen on the machining of AISI H13 by using design of experiment. The main objectives of this work are to investigate the process parameters for surface roughness and tool wear in end milling to obtain the optimal surface roughness and tool wear using Response Surface Methodology and to recommend the best machining parameters that contributes to the optimum surface roughness and tool wear value.

Index Terms—Response Surface Methodology (RSM), Mathematical modeling, Surface roughness (Ra), Tool wear and surface plots

Cite: Anmol Kumar and M K Paswan, "Optimization of Cutting Parameters of AlSI H13 with Multiple Performance Characteristics," International Journal of Mechanical Engineering and Robotics Research, Vol.2 No.3, pp. 45-54, July 2013.