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Multi Response Optimization of Setting Process Variables in Face Milling of ZE41 Magnesium Alloy using Ranking Algorithms and ANOVA


Affiliations
1 Dept. of Mech. Engg., SRM Institute of Sci. and Tech., Kattankulathur, Tamil Nadu, India
2 SRM Institute of Sci. and Tech., Kattankulathur, Tamil Nadu, India
3 Dept. of Mechatronics Engg., ISHIK University, ERBIL, KRG, India
4 Dept. of Mechatronics Engg., SRM Institute of Sci. and Tech., Kattankulathur, Tamil Nadu, India
 

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This study presents the optimization of machining parameters on ZE41 Mg alloy fabricated by gravity die casting and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Focus on the optimization of machining parameters using the technique to get minimum surface roughness, cutting force, thermal stress, residual stress, chip thickness and maximum MRR. A number of machining experiments were conducted based on the L27 orthogonal array on computer numerical control vertical machining center. The experiments were performed on ZE41 using cutting tool of an ISO 460. 1-1140-034A0-XM GC3 of 20, 25 and 30mm diameter with cutting point 140 degrees, for different cutting conditions. TOPSIS and ANOVA were used to work out the fore most important parameters cutting speed, feed rate, depth of cut and tool diameter which affect the response. The expected values and measured values are fairly close. Finally, the study for optimizing machining process is surveyed and results show improvement in real experiments.

Keywords

Mg Alloy, Different Cutting Conditions, TOPSIS, ANOVA, Machining, L27 Array.
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  • J.P. Davim. 2003. Study of machining metal-matrix composites based on the Taguchi techniques, J. Mater. Process Tech., 132, 250-254. https://doi.org/10.1016/S0924-0136(02)00935-4.

  • Mustafa and K. Ki. 2008. Magnesium and its alloys applications in automotive industry, Int. J. Adv. Manuf. Tech., 39, 851-865. https://doi.org/10.1007/s00170-007-1279-2.

  • A. Eliezer, J. Haddad, Y. Unigovski and E.M. Gutman. 2005. Static and dynamic corrosion fatigue of Mg alloys used in automotive industry, Materials and Manuf. Processes, 20, 75-88. https://doi.org/10.1081/AMP200041636.

  • F.C. Campbell. 2006. Manuf. Tech. for Aerospace Structure Material, Elsevier Press, UK.

  • R. Ambat and W. Zhou. 2004. Electro-less nickel-plating on AZ91D magnesium alloy: Effect of substrate microstructure and plating parameters, Surface and Coatings Tech., 179, 124-134. https://doi.org/10.1016/S0257-8972(03)00866-1.

  • Y.J. Huang, B.H. Hu, I. Pinwill, W. Zhou and D.M.R. Taplin. 2000. Effects of process setting on the porosity levels of AM60B magnesium die castings, Materials and Manuf. Processes, 15, 97-105. https://doi.org/10.1080/10426910008912975.

  • H. Henry, Y. Alfred, L. Naiyi and E.A. John. 2003. Potential magnesium alloys for high temperature die cast automotive applications: A review, Materials and Manuf. Processes, 18, 687-717. https://doi.org/10.1081/AMP120024970.

  • K.U. Kainer and F. Buch. 1999. Modern development of alloys for light weight components, Material Sci. and Materials Engg., 30, 159-167.

  • P.S. Sreejith and B.K.A. Ngoi. 2000. Dry machining: Machining of the future, J. Materials Processing Tech., 101, 287-291. https://doi.org/10.1016/S0924-0136(00) 00445-3.

  • N.A. Abukhshim, P.T. Mativenga and M.A. Sheikh. 2006. Heat generation and temperature prediction in metal cutting: A review and implications for high speed machining, Int. J. Machine Tools and Manuf., 46, 782-800. https://doi.org/10.1016/j.ijmachtools.2005.07.024.

  • T. Kitagawa, A. Kubo and K. Maekawa. 1997. Temperature and wear of cutting tools in high-speed machining of Inconel 718 and Ti-6Al-6V-2Sn, Wear, 202(2), 142-148. https://doi.org/10.1016/S0043-1648 (96)07255-9.

  • R. Schirsch, D. Thamke and W. Zielasko. 1998 Economics of dry machining, VDIB Reports, 1375, 371-397.

  • K. Weinert, F.J. Adams and D. Thamke. 1995. What is the cost of cooling lubrication?, Technica, 44(7), 19-23.

  • D. Thamke. 1998 Technological and Economic Aspects of Dry and Minimum Quantity Processing using the Example of Single Lip Deep Drilling, Ph.D Thesis, University of Dortmund, Germany.

  • H. Kissler. 2000. KSS-related costs in metalworking as an incentive for dry machining, Proc.12th Int. Colloquium Tribology, 2, 901913.

  • Z. Chen, K. Wong, W. Li, D.A. Stephenson and S.Y. Liang. 1999. Cutting fluid aerosol generation due to spinoff in turning operation, Proc., ASME, Manuf. Sci. and Engg., 10, 285-291.

  • K.L. Gunter, J.W. Sutherland. 1999. An experimental investigation into the effect of process conditions on the mass concentration of cutting fluid mist in turning, J. Cleaner Production, 7(5), 341-350. https://doi.org/10.1016/S0959-6526(99)00150-X.

  • D.M. Hands, J. Sheehan, B. Wong and H.B. Lick. 1996. Comparison of metalworking fluid mist exposures from machining with different levels of machine enclosure, American Industrial Hygiene Association J., 57(12), 1173-1178. https://doi.org/10.1080/15428119691014305.

  • T.D. Howes, H.K. Tönshoff and W. Heuer. 1991. Environmental aspects of grinding fluids, Annals of the CIRP, 40(2), 623-630. https://doi.org/10.1016/S0007-8506(07)61138-X.

  • H.W. Rossmoore. 1995. Microbiology of metalworking fluids: deterioration, disease, and disposal, Lubrication Engg., 51(2), 113-130.

  • R.B. Aronson. 1995. Why Dry Machining, Manufa. Engg., 114(1), 33-36.

  • F. Klocke, D. Lung and G. Eisenblätter. 1996. Low-volume cooling lubrication an alternative to wet processing?, VDI Reports, 1240, 159190.

  • S.P.S.S. Sivam, V.G. Umasekar, S. Mishra, A. Mishra and A. Mondal. 2016. Orbital cold forming technology combining high quality forming with cost effectiveness A review, Indian J. Sci. Tech., 9(38), 1-7. https://doi.org/10.17485/ijst/2016/v9i38/91426.

  • J.W. Sutherland, V.N. Kulur and N.C. King. 2000. An experimental investigation of air quality in wet and dry turning, Annals of CIRP, 49(1), 61-64. https://doi.org/10.1016/S0007-8506(07)62896-0.

  • S.P.S.S. Sivam, V.G. Umasekar, K. Saravanan, S. Rajendrakumar, P. Karthikeyan, K.S. Moorthy. 2016. Frequently used anisotropic yield criteria for sheet metal applications: A review, Indian J. Sci. and Tech. 9(47), 1-6. https://doi.org/10.17485/ijst/2015/v8i1/92107.

  • C.M. Daniel, W.W. Olson and J.W. Sutherland. 1997. Research advances in dry and semi-dry machining, SAE , J. Materials and Manuf., 106, 373-383.

  • S.P.S.S. Sivam, M. Gopal, S. Venkatasamy and S. Singh. 2015. An experimental investigation and optimisation of ecological machining parameters on aluminium 6063 in its annealed and unannealed form, J. Chemical and Pharmaceutical Scis., 9, 46-53.

  • W. König. 1999. Manufacturing Process I - Turning, Milling, Drilling, Springer-Verlag, Berlin Heidelberg.

  • S.P.S.S. Sivam, A. Lakshmankumar, K.S. Moorthy and S. Rajendrakumar. 2015. Investigation exploration outcome of heat treatment on corrosion resistance of AA 5083 in marine application, Int. J. Chemical Sci., 14(S2), 453-460.

  • S.P.S.S. Sivam, M.D.J. Bhat, S. Natarajan and N. Chauhan. 2018. Analysis of residual stresses, thermal stresses, cutting forces and other output responses of face milling operation on Ze41 magnesium alloy, Int. J. Modern Manuf. Tech., 10(1), 92-100.

  • S.P.S.S. Sivam, K. Saravanan, N. Pradeep, K. Moorthy and S. Rajendrakumar. 2018. The grey relational analysis and ANOVA to determine the optimum process parameters for friction stir welding of Ti and Mg alloys, Periodica Polytechnica Mech. Engg., 62(4), 277-283. https://doi.org/10.3311/PPme.12117.

  • S.P.S.S. Sivam, K.S. Moorthy, B.K. Yedida, J.R. Atluri and S. Mathur. 2017. Multi response optimization of setting input variables for getting better product quality in machining of magnesium AM60 by grey relation analysis and ANOVA, Periodica Polytechnica Mech. Engg., 62(2), 118-125. https://doi.org/10.3311/PPme.11034.


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  • Multi Response Optimization of Setting Process Variables in Face Milling of ZE41 Magnesium Alloy using Ranking Algorithms and ANOVA

Abstract Views: 672  |  PDF Views: 236

Authors

S. P. Sundar Singh Sivam
Dept. of Mech. Engg., SRM Institute of Sci. and Tech., Kattankulathur, Tamil Nadu, India
V. G. Umasekar
SRM Institute of Sci. and Tech., Kattankulathur, Tamil Nadu, India
Ganesh Babu Loganathan
Dept. of Mechatronics Engg., ISHIK University, ERBIL, KRG, India
D. Kumaran
SRM Institute of Sci. and Tech., Kattankulathur, Tamil Nadu, India
K. Saravanan
Dept. of Mechatronics Engg., SRM Institute of Sci. and Tech., Kattankulathur, Tamil Nadu, India

Abstract


This study presents the optimization of machining parameters on ZE41 Mg alloy fabricated by gravity die casting and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Focus on the optimization of machining parameters using the technique to get minimum surface roughness, cutting force, thermal stress, residual stress, chip thickness and maximum MRR. A number of machining experiments were conducted based on the L27 orthogonal array on computer numerical control vertical machining center. The experiments were performed on ZE41 using cutting tool of an ISO 460. 1-1140-034A0-XM GC3 of 20, 25 and 30mm diameter with cutting point 140 degrees, for different cutting conditions. TOPSIS and ANOVA were used to work out the fore most important parameters cutting speed, feed rate, depth of cut and tool diameter which affect the response. The expected values and measured values are fairly close. Finally, the study for optimizing machining process is surveyed and results show improvement in real experiments.

Keywords


Mg Alloy, Different Cutting Conditions, TOPSIS, ANOVA, Machining, L27 Array.

References





DOI: https://doi.org/10.4273/ijvss.11.1.10