Investigating the effects of electric discharge machining parameters on material removal rate and surface roughness on AISI D2 steel using RSM-GRA integrated approach
The present research focuses on optimizing the process parameters of die-sinking electric discharge machining on tool steel. The basic objective of this research is to investigate the influence of two categorical factors including dielectric type and electrode polarity, and two numeric factors inclu...
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Published in | International journal of advanced manufacturing technology Vol. 101; no. 5-8; pp. 1255 - 1265 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
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Springer London
01.04.2019
Springer Nature B.V |
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Abstract | The present research focuses on optimizing the process parameters of die-sinking electric discharge machining on tool steel. The basic objective of this research is to investigate the influence of two categorical factors including dielectric type and electrode polarity, and two numeric factors including discharge current, and Spark/Discharge Gap on material removal rate (MRR) and surface roughness (
R
a
) for machining of AISI D2 steel. Box-Bhenken design based on response surface methodology (RSM) was applied for experimental design. For estimation and evaluation, the effects of the process parameters on response variables, RSM has been integrated with grey relational analysis (GRA). Ranking of factors has been done with respect to the grey relational grade. (ANOVA) was further performed for determining the significance of grey relational grade. ANOVA results reveal that that polarity having 50% of percentage contribution was the most significant factor affecting the performance measures followed by the spark gap, discharge current, and dielectric type. The grey relational grades were further optimized through desirability function and the optimal condition for input parameters was obtained. The optimum levels were discharge current at 15 A, dielectric type of kerosene oil, spark gap at 6 mm, and polarity of positive has been determined. The confirmatory tests were run for verifying and validating the results and improvement in productivity (MRR) up to 17.23 mm
3
/min and quality (
R
a
) up to 3.86 μm at an optimum have been observed. |
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AbstractList | The present research focuses on optimizing the process parameters of die-sinking electric discharge machining on tool steel. The basic objective of this research is to investigate the influence of two categorical factors including dielectric type and electrode polarity, and two numeric factors including discharge current, and Spark/Discharge Gap on material removal rate (MRR) and surface roughness (
R
a
) for machining of AISI D2 steel. Box-Bhenken design based on response surface methodology (RSM) was applied for experimental design. For estimation and evaluation, the effects of the process parameters on response variables, RSM has been integrated with grey relational analysis (GRA). Ranking of factors has been done with respect to the grey relational grade. (ANOVA) was further performed for determining the significance of grey relational grade. ANOVA results reveal that that polarity having 50% of percentage contribution was the most significant factor affecting the performance measures followed by the spark gap, discharge current, and dielectric type. The grey relational grades were further optimized through desirability function and the optimal condition for input parameters was obtained. The optimum levels were discharge current at 15 A, dielectric type of kerosene oil, spark gap at 6 mm, and polarity of positive has been determined. The confirmatory tests were run for verifying and validating the results and improvement in productivity (MRR) up to 17.23 mm
3
/min and quality (
R
a
) up to 3.86 μm at an optimum have been observed. The present research focuses on optimizing the process parameters of die-sinking electric discharge machining on tool steel. The basic objective of this research is to investigate the influence of two categorical factors including dielectric type and electrode polarity, and two numeric factors including discharge current, and Spark/Discharge Gap on material removal rate (MRR) and surface roughness (Ra) for machining of AISI D2 steel. Box-Bhenken design based on response surface methodology (RSM) was applied for experimental design. For estimation and evaluation, the effects of the process parameters on response variables, RSM has been integrated with grey relational analysis (GRA). Ranking of factors has been done with respect to the grey relational grade. (ANOVA) was further performed for determining the significance of grey relational grade. ANOVA results reveal that that polarity having 50% of percentage contribution was the most significant factor affecting the performance measures followed by the spark gap, discharge current, and dielectric type. The grey relational grades were further optimized through desirability function and the optimal condition for input parameters was obtained. The optimum levels were discharge current at 15 A, dielectric type of kerosene oil, spark gap at 6 mm, and polarity of positive has been determined. The confirmatory tests were run for verifying and validating the results and improvement in productivity (MRR) up to 17.23 mm3/min and quality (Ra) up to 3.86 μm at an optimum have been observed. |
Author | Shah, Abdul Hakim Jahanzaib, Mirza Hanif, Muhammad Ahmad, Wasim Hussain, Salman |
Author_xml | – sequence: 1 givenname: Muhammad surname: Hanif fullname: Hanif, Muhammad organization: Department of Industrial Engineering, University of Engineering and Technology Taxila – sequence: 2 givenname: Wasim surname: Ahmad fullname: Ahmad, Wasim organization: Department of Industrial Engineering, University of Engineering and Technology Taxila – sequence: 3 givenname: Salman surname: Hussain fullname: Hussain, Salman organization: Department of Industrial Engineering, University of Engineering and Technology Taxila – sequence: 4 givenname: Mirza surname: Jahanzaib fullname: Jahanzaib, Mirza organization: Department of Industrial Engineering, University of Engineering and Technology Taxila – sequence: 5 givenname: Abdul Hakim surname: Shah fullname: Shah, Abdul Hakim email: dr.abdulhakim@kkkuk.edu.pk organization: Department of Physics, Khushal Khan Khattak University Karak |
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Keywords | Surface roughness Die-sinking EDM Material removal rate AISI D2 steel RSM GRA |
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SubjectTerms | CAE) and Design Chromium molybdenum vanadium steels Computer-Aided Engineering (CAD Design of experiments Die sinking Dielectrics Electric discharge machining Engineering Industrial and Production Engineering Integrated approach Kerosene Material removal rate (machining) Mechanical Engineering Media Management Optimization Original Article Polarity Process parameters Process planning Response surface methodology Surface roughness Tool steels Variance analysis |
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Title | Investigating the effects of electric discharge machining parameters on material removal rate and surface roughness on AISI D2 steel using RSM-GRA integrated approach |
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