Parametric Optimization of Tool Wear Rate in Side Flushing form of Die Sink EDM of EN-31 Die Steel

Authors

  • Navdeep Malhotra Shri Mata Vaishno Devi University, Katra, J & K, India
  • Dr. Sona Rani UIET, Kurukshetra University, Kurukshetra, Haryana, India.

Keywords:

EDM, Side Flushing, Taguchi Methodology, TWR

Abstract

Electrical discharge machining (EDM) is one of the most extensively used non-conventional material removal processes for manufacturing geometrically complex or hard material parts that are extremely difficult to machine by conventional machining process. EDM researchers have concentrated on achieving faster and more efficient metal removal rate coupled with a reduction in tool wear and improved surface characteristics. In this paper, the operating performance measures of side flushing type of electrical discharge machining process on EN-31 die steel using copper electrode are being optimized considering one of its effective machining parameter i.e. Tool Wear Rate (TWR). Tool wear is one of the major quality characteristic among others i.e. material removal rate, surface finish etc. to be optimized because of in EDM process tool cost is approximately 70% of the total operating cost. In this paper an L27 orthogonal array of Taguchi methodology has been used to identify the effect of process input factors and their interactions (viz. voltage, current, spark gap, pulse on time, duty cycle and flushing pressure) on tool wear rate. Hence, the quality characteristic for TWR is set to lower- the-better to attain the optimum dimensional precision. Using Taguchi’s parameter design, significant machining parameters affecting the tool wear rate are identified as current (58.95%), pulse on time, spark gap, voltage and duty cycle while the flushing pressure as no significant effect on tool wear rate. The predicted tool wear rate is calculated as 0.004g/min and further verified by conducting confirmation experiments at selected parameters. The result of average of three experiments 0.00419g/min is obtained. The variation between predicted and experimental value is within 3% and this shows that the developed model is valid /acceptable for similar process.

Author Biographies

  • Navdeep Malhotra, Shri Mata Vaishno Devi University, Katra, J & K, India
    Assistant Professor, School of Mechanical Engineering
  • Dr. Sona Rani, UIET, Kurukshetra University, Kurukshetra, Haryana, India.
    Assistant Professor, CSE

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Published

2019-04-18

Issue

Vol. 1 No. 1-3 (2011)

Section

Articles

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