Parameter optimisation to combine low energy consumption with high surface integrity in turning Mg/Al2O3 hybrid composites under dry and MQL conditions

  • E. SuneeshEmail author
  • M. Sivapragash
Technical Paper


A high strength-to-mass ratio makes the use of metal matrix composites acceptable for a wide range of engineering applications. However, their use is often complicated, and machining such composites involves several challenges. During the machining process, controllable machining parameters need to be optimised to achieve multiple objectives. In this work, an attempt was made to streamline the turning parameters of a magnesium/alumina hybrid composite under dry and minimum quantity lubrication (MQL) cutting conditions. Experiments were carried out based on Taguchi’s L18 orthogonal array. The input parameters (i.e. cutting conditions, cutting speed, feed and depth of the cut) were considered the cutting factors, while surface roughness, cutting force, specific power consumption, and cutting temperature were the response variables. A grey relational analysis (GRA) and the techniques for order preferences by similarity to ideal solution (TOPSIS) method were employed to improve the straight turning process of hybrid composites and to optimise the input control factors. The percentage contribution of each input parameter was identified by creating an analysis of variance (ANOVA) table. Based on the data given in the response table and the ANOVA table for the GRA and TOPSIS, feed rate was found to be the most influential parameter of those investigated in the present study, followed by the depth of cut, cutting conditions, and cutting speed. The GRA and TOPSIS produced two unique sets of optimised parameters. The optimised parameter combinations obtained using the GRA method were cutting condition = MQL, cutting speed = 100 m/min, feed rate = 0.15 mm/rev, and depth of cut = 0.50 mm; using the TOPSIS, the optimal value for cutting speed changed to 150 m/min when all other parameter values were kept the same as they were for the GRA. However, from the results of the validation tests, it was clear that the optimised parameters obtained from the TOPSIS produced a machined composite with better properties than the composite produced using the GRA.


Turning Magnesium hybrid composite Quality characteristics Taguchi method Grey relational analysis TOPSIS 



Authors would like to acknowledge the facilities, scientific and technical assistance from Vidya Academy of Science and Technology, Thrissur, Kerala and NICHE, Kumaracoil, Tamil Nadu.

Data availability

The raw/processed data required to reproduce these findings cannot be shared at this time as the data also forms part of an ongoing study.

Funding information

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Compliance with ethical standards

Conflicts of interest

Authors have no conflicts of interest.


  1. 1.
    Beck AV (ed) (1943) The technology of magnesium and its alloys. FA Hughes & Company Limited, LondonGoogle Scholar
  2. 2.
    Hirsch J, Al-Samman T (2013) Superior light metals by texture engineering: optimized aluminum and magnesium alloys for automotive applications. Acta Mater 61(3):818–843CrossRefGoogle Scholar
  3. 3.
    Thein MA, Lu L, Lai MO (2009) Effect of milling and reinforcement on mechanical properties of nanostructured magnesium composite. J Mater Process Technol 209(9):4439–4443CrossRefGoogle Scholar
  4. 4.
    Kainer KU, Dieringa H, Dietzel W, Hort N, Blawert C (2006) The use of magnesium alloys: past, present and future. In: Proceedings of the magnesium technology in the global age, international symposium, COM 2006, 45th annual conference of metallurgists of CIM, Montreal, CN, 1–4 Oct 2006. Fraunhofer IRB Verlag, Stuttgart, pp 3–19. ISBN: 1-894475-66-6Google Scholar
  5. 5.
    Bettles C, Gibson M (2005) Current wrought magnesium alloys: strengths and weaknesses. J Mater 57(5):46–49Google Scholar
  6. 6.
    Suneesh E, Sivapragash M (2018) Comprehensive studies on processing and characterization of hybrid magnesium composites. Mater Manuf Process 33(12):1324–1345CrossRefGoogle Scholar
  7. 7.
    Eacherath S, Murugesan S (2018) Synthesis and characterization of magnesium-based hybrid composites—a review. Int J Mater Res 109(7):661–672CrossRefGoogle Scholar
  8. 8.
    Goh CS, Wei J, Lee LC, Gupta M (2005) Development of novel carbon nanotube reinforced magnesium nanocomposites using the powder metallurgy technique. Nanotechnology 17(1):7CrossRefGoogle Scholar
  9. 9.
    Kvashnin DG, Krasheninnikov AV, Shtansky D, Sorokin PB, Golberg D (2016) Nanostructured BN–Mg composites: features of interface bonding and mechanical properties. Phys Chem Chem Phys 18(2):965–969CrossRefGoogle Scholar
  10. 10.
    Wang XJ, Wang NZ, Wang LY, Hu XS, Wu K, Wang YQ, Huang YD (2014) Processing, microstructure and mechanical properties of micro-SiC particles reinforced magnesium matrix composites fabricated by stir casting assisted by ultrasonic treatment processing. Mater Des 57:638–645CrossRefGoogle Scholar
  11. 11.
    Sankaranarayanan S, Habibi MK, Jayalakshmi S, Jia Ai K, Almajid A, Gupta M (2015) Nano-AlN particle reinforced Mg composites: microstructural and mechanical properties. Mater Sci Technol 31(9):1122–1131CrossRefGoogle Scholar
  12. 12.
    Lloyd DJ (1994) Particle reinforced aluminium and magnesium matrix composites. Int Mater Rev 39(1):1–23CrossRefGoogle Scholar
  13. 13.
    Ibrahim IA, Mohamed FA, Lavernia EJ (1991) Particulate reinforced metal matrix composites—a review. J Mater Sci 26(5):1137–1156CrossRefGoogle Scholar
  14. 14.
    Zhang Z, Han BQ, Witkin D, Ajdelsztajn L, Laverna EJ (2006) Synthesis of nanocrystalline aluminum matrix composites reinforced with in situ devitrified Al–Ni–La amorphous particles. Scr Mater 54(5):869–874CrossRefGoogle Scholar
  15. 15.
    Sankaranarayanan S, Shankar VH, Jayalakshmi S, Bau NQ, Gupta M (2015) Development of high performance magnesium composites using Ni50Ti50 metallic glass reinforcement and microwave sintering approach. J Alloy Compd 627:192–199CrossRefGoogle Scholar
  16. 16.
    Tun KS, Gupta M (2007) Improving mechanical properties of magnesium using nano-yttria reinforcement and microwave assisted powder metallurgy method. Compos Sci Technol 67(13):2657–2664CrossRefGoogle Scholar
  17. 17.
    Paramsothy M, Hassan SF, Srikanth N, Gupta M (2009) Enhancing tensile/compressive response of magnesium alloy AZ31 by integrating with Al2O3 nanoparticles. Mater Sci Eng A 527(1–2):162–168CrossRefGoogle Scholar
  18. 18.
    Hassan SF, Gupta M (2004) Development of high performance magnesium nanocomposites using solidification processing route. Mater Sci Technol 20(11):1383–1388CrossRefGoogle Scholar
  19. 19.
    Hassan SF, Gupta M (2005) Development of high performance magnesium nano-composites using nano-Al2O3 as reinforcement. Mater Sci Eng A 392(1–2):163–168CrossRefGoogle Scholar
  20. 20.
    Hassan SF, Gupta M (2006) Effect of different types of nano-size oxide particulates on microstructural and mechanical properties of elemental Mg. J Mater Sci 41(8):2229–2236CrossRefGoogle Scholar
  21. 21.
    Wong WLE, Karthik S, Gupta M (2005) Development of hybrid Mg/Al2O3 composites with improved properties using microwave assisted rapid sintering route. J Mater Sci 40(13):3395–3402CrossRefGoogle Scholar
  22. 22.
    Hou J, Zhao N, Zhu S (2011) Influence of cutting speed on flank temperature during face milling of magnesium alloy. Mater Manuf Process 26(8):1059–1063CrossRefGoogle Scholar
  23. 23.
    Rubio EM, Villeta M, Carou D, Saá A (2014) Comparative analysis of sustainable cooling systems in intermittent turning of magnesium pieces. Int J Precis Eng Manuf 15(5):929–940CrossRefGoogle Scholar
  24. 24.
    Villeta M, de Agustina B, de Pipaón JMS, Rubio EM (2012) Efficient optimisation of machining processes based on technical specifications for surface roughness: application to magnesium pieces in the aerospace industry. Int J Adv Manuf Technol 60(9–12):1237–1246CrossRefGoogle Scholar
  25. 25.
    Fang FZ, Lee LC, Liu XD (2005) Mean flank temperature measurement in high speed dry cutting of magnesium alloy. J Mater Process Technol 167(1):119–123CrossRefGoogle Scholar
  26. 26.
    Singh S (2016) Study the drilling behaviour of aluminium 6061 metal matrix composites using Taguchi’s methodology. Int J Mach Mach Mater 18(4):327–340Google Scholar
  27. 27.
    Mohan B, Rajadurai A, Satyanarayana KG (2004) Electric discharge machining of Al–SiC metal matrix composites using rotary tube electrode. J Mater Process Technol 153:978–985CrossRefGoogle Scholar
  28. 28.
    Gok A (2015) A new approach to minimization of the surface roughness and cutting force via fuzzy TOPSIS, multi-objective grey design and RSA. Measurement 70:100–109CrossRefGoogle Scholar
  29. 29.
    Wang MY, Chang HY (2004) Experimental study of surface roughness in slot end milling AL2014-T6. Int J Mach Tools Manuf 44(1):51–57CrossRefGoogle Scholar
  30. 30.
    Puertas I, Luis CJ (2004) A study of optimization of machining parameters for electrical discharge machining of boron carbide. Mater Manuf Process 19(6):1041–1070CrossRefGoogle Scholar
  31. 31.
    Saikumar S, Shunmugam MS (2006) Parameter selection based on surface finish in high-speed end-milling using differential evolution. Mater Manuf Process 21(4):341–347CrossRefGoogle Scholar
  32. 32.
    Kıvak T (2014) Optimization of surface roughness and flank wear using the Taguchi method in milling of Hadfield steel with PVD and CVD coated inserts. Measurement 50:19–28CrossRefGoogle Scholar
  33. 33.
    Rubio EM, Valencia JL, Saá AJ, Carou D (2013) Experimental study of the dry facing of magnesium pieces based on the surface roughness. Int J Precis Eng Manuf 14(6):995–1001CrossRefGoogle Scholar
  34. 34.
    Villeta M, Rubio EM, De Pipaón JS, Sebastián MA (2011) Surface finish optimization of magnesium pieces obtained by dry turning based on Taguchi techniques and statistical tests. Mater Manuf Process 26(12):1503–1510CrossRefGoogle Scholar
  35. 35.
    De Pipaon JS, Rubio E, Villeta M, Sebastian M (2008) Influence of cutting conditions and tool coatings on the surface finish of workpieces of magnesium obtained by dry turning. In: Annals of DAAAM & proceedings, pp 1207–1209Google Scholar
  36. 36.
    Sáenz De Pipaón JM, Rubio EM, Viletta M, Sebastián MA (2009) Improved model for estimating the expected roughness in dry turning of magnesium UNS M11311. In: Annals of DAAAM for 2009 & proceedings of the 20th international DAAAM symposium” intelligent manufacturing & automation: focus on theory, practice and education, vol 20, No 1, pp 319–320)Google Scholar
  37. 37.
    Wang Q, Liu F, Wang X (2014) Multi-objective optimization of machining parameters considering energy consumption. Int J Adv Manuf Technol 71(5–8):1133–1142CrossRefGoogle Scholar
  38. 38.
    Viswanathan R, Ramesh S, Subburam V (2018) Measurement and optimization of performance characteristics in turning of Mg alloy under dry and MQL conditions. Measurement 120:107–113CrossRefGoogle Scholar
  39. 39.
    Davim JP, Sreejith PS, Silva J (2007) Turning of brasses using minimum quantity of lubricant (MQL) and flooded lubricant conditions. Mater Manuf Process 22(1):45–50CrossRefGoogle Scholar
  40. 40.
    Zhang S, Li JF, Wang YW (2012) Tool life and cutting forces in end milling Inconel 718 under dry and minimum quantity cooling lubrication cutting conditions. J Clean Prod 32:81–87CrossRefGoogle Scholar
  41. 41.
    Attanasio A, Gelfi M, Giardini C, Remino C (2006) Minimal quantity lubrication in turning: effect on tool wear. Wear 260(3):333–338CrossRefGoogle Scholar
  42. 42.
    Carou D, Rubio EM, Lauro CH, Davim JP (2016) The effect of minimum quantity lubrication in the intermittent turning of magnesium based on vibration signals. Measurement 94:338–343CrossRefGoogle Scholar
  43. 43.
    Carou D, Rubio EM, Davim JP (2015) A note on the use of the minimum quantity lubrication (MQL) system in turning. Ind Lubr Tribol 67(3):256–261CrossRefGoogle Scholar
  44. 44.
    Davim JP, Sreejith PS, Gomes R, Peixoto C (2006) Experimental studies on drilling of aluminium (AA1050) under dry, minimum quantity of lubricant, and flood-lubricated conditions. Proc Inst Mech Eng Part B J Eng Manuf 220(10):1605–1611CrossRefGoogle Scholar
  45. 45.
    Gaitonde VN, Karnik SR, Davim JP (2012) Optimal MQL and cutting conditions determination for desired surface roughness in turning of brass using genetic algorithms. Mach Sci Technol 16(2):304–320CrossRefGoogle Scholar
  46. 46.
    Gupta K, Laubscher RF, Davim JP, Jain NK (2016) Recent developments in sustainable manufacturing of gears: a review. J Clean Prod 112:3320–3330CrossRefGoogle Scholar
  47. 47.
    Deng JL (1989) Introduction to Grey system theory. J Grey Syst 1(1):1–24MathSciNetzbMATHGoogle Scholar
  48. 48.
    Opricovic S, Tzeng GH (2004) Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. Eur J Oper Res 156(2):445–455zbMATHCrossRefGoogle Scholar
  49. 49.
    Buldum B, Eşme U, Kemal Külekci M, Şik A, Kazançoğlu Y (2012) Use of Grey-Taguchi method for the optimization of oblique turning process of AZ91D magnesium alloy. Mater Test 54(11–12):779–785CrossRefGoogle Scholar
  50. 50.
    Gopal PM, Prakash KS (2018) Minimization of cutting force, temperature and surface roughness through GRA, TOPSIS and Taguchi techniques in end milling of Mg hybrid MMC. Measurement 116:178–192CrossRefGoogle Scholar
  51. 51.
    Lalwani DI, Mehta NK, Jain PK (2008) Experimental investigations of cutting parameters influence on cutting forces and surface roughness in finish hard turning of MDN250 steel. J Mater Process Technol 206(1–3):167–179CrossRefGoogle Scholar
  52. 52.
    Pawade RS, Sonawane HA, Joshi SS (2009) An analytical model to predict specific shear energy in high-speed turning of Inconel 718. Int J Mach Tools Manuf 49(12–13):979–990CrossRefGoogle Scholar
  53. 53.
    Motorcu AR, Isik Y, Kus A, Cakir MC (2016) Analysis of the cutting temperature and surface roughness during the orthogonal machining of AISI 4140 alloy steel via the Taguchi method. Analysis 343:351Google Scholar
  54. 54.
    Suneesh E, Sivapragash M (2017) Mechanical performance of magnesium composites containing hybrid Al2O3 reinforcement. Int J Civ Eng Technol (IJCIET) 8(8):365–378Google Scholar
  55. 55.
    El-Hofy HAG (2013) Fundamentals of machining processes: conventional and nonconventional processes. CRC Press, Boca RatonCrossRefGoogle Scholar
  56. 56.
    Mia M, Dhar NR (2017) Optimization of surface roughness and cutting temperature in high-pressure coolant-assisted hard turning using Taguchi method. Int J Adv Manuf Technol 88(1–4):739–753CrossRefGoogle Scholar
  57. 57.
    Mia M, Rifat A, Tanvir MF, Gupta MK, Hossain MJ, Goswami A (2018) Multi-objective optimization of chip-tool interaction parameters using Grey-Taguchi method in MQL-assisted turning. Measurement 129:156–166CrossRefGoogle Scholar
  58. 58.
    Mia M, Al Bashir M, Khan MA, Dhar NR (2017) Optimization of MQL flow rate for minimum cutting force and surface roughness in end milling of hardened steel (HRC 40). Int J Adv Manuf Technol 89(1–4):675–690CrossRefGoogle Scholar
  59. 59.
    Srinivasan L, Chand KM, Kannan TDB, Sathiya P, Biju S (2018) Application of GRA and TOPSIS optimization techniques in GTA welding of 15CDV6 aerospace material. Trans Indian Inst Met 71(2):373–382CrossRefGoogle Scholar
  60. 60.
    Kilickap E, Yardimeden A, Çelik YH (2017) Mathematical modelling and optimization of cutting force, tool wear and surface roughness by using artificial neural network and response surface methodology in milling of Ti-6242S. Appl Sci 7(10):1064CrossRefGoogle Scholar
  61. 61.
    Çiçek A, Kıvak T, Ekici E (2015) Optimization of drilling parameters using Taguchi technique and response surface methodology (RSM) in drilling of AISI 304 steel with cryogenically treated HSS drills. J Intell Manuf 26(2):295–305CrossRefGoogle Scholar
  62. 62.
    Eker B, Ekici B, Kurt M, Bakır B (2014) Sustainable machining of the magnesium alloy materials in the CNC lathe machine and optimization of the cutting conditions. Mechanics 20(3):310–316CrossRefGoogle Scholar
  63. 63.
    Williams JA, Tabor D (1977) The role of lubricants in machining. Wear 43(3):275–292CrossRefGoogle Scholar
  64. 64.
    Hong SY, Ding Y (2001) Cooling approaches and cutting temperatures in cryogenic machining of Ti-6Al-4V. Int J Mach Tools Manuf 41(10):1417–1437CrossRefGoogle Scholar
  65. 65.
    Gupta MK, Sood PK, Singh G, Sharma VS (2017) Experimental investigation and optimization on MQL-assisted turning of Inconel-718 super alloy. In: Advanced manufacturing technologies, pp 237–248. Springer, ChamGoogle Scholar
  66. 66.
    Stephenson DA, Agapiou JS (2016) Metal cutting theory and practice. CRC Press, Boca RatonCrossRefGoogle Scholar
  67. 67.
    Sivasakthivel PS, Sudhakaran R (2013) Optimization of machining parameters on temperature rise in end milling of Al 6063 using response surface methodology and genetic algorithm. Int J Adv Manuf Technol 67(9–12):2313–2323CrossRefGoogle Scholar
  68. 68.
    Wojciechowski S, Maruda RW, Krolczyk GM, Niesłony P (2018) Application of signal to noise ratio and grey relational analysis to minimize forces and vibrations during precise ball end milling. Precis Eng 51:582–596CrossRefGoogle Scholar

Copyright information

© The Brazilian Society of Mechanical Sciences and Engineering 2019

Authors and Affiliations

  1. 1.Department of Production EngineeringVidya Academy of Science & TechnologyThrissurIndia
  2. 2.Department of Mechanical EngineeringPSN College of Engineering & TechnologyTirunelveliIndia

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