Performance of water-based TiO2 nanofluid during the minimum quantity lubrication machining of aluminium alloy, AA6061-T6

Abstract The effects of cutting parameters on the wear mechanisms in the end milling of aluminium alloy AA6061 with minimum quantity lubrication (MQL) conditions using water-based TiO2 nanofluid were investigated. Three different cutting speeds of 5200, 5400 and 5600 rpm were used. The MQL flow rates used were 0.65 ml/min and 1.0 ml/min, while the TiO2 nanoparticles used were of different volume fractions in the aqueous solutions of 0.5, 2.5 and 4.5%. The results showed that the adhesion of the work material is the major tool damage phenomenon. In addition, abrasion was observed. The major benefit from the water-based nanofluid MQL was shown in the edge integrity i.e., edge chipping and edge fracture were seen in very few cases especially with a higher depth of cut higher. This is attributed to the cooling effect produced by the latent heat of vaporization of the water resulting in the lowering of temperature in the cutting zone. The volume fraction of 2.5% TiO2 nanoparticles appeared more feasible in terms of tool damage. The effectiveness of the non-conventional nanofluid MQL was also discussed. A non-deterministic component of the sustainability index, for the milling process with the MQL, was calculated using fuzzy logic. The basic objective is to quantify the non-deterministic component of the sustainability index by using the fuzzy rule-based model for the performance analysis of machining with MQL. The results show the prospective utilization of water-based TiO2 nanofluid as the MQL medium. Thus, it is beneficial for the higher cooling rates of water integrated with the lubrication characteristics of nanoparticles.

[1]  P Vamsi Krishna,et al.  Experimental investigations on influence of mist cooling using nanofluids on machining parameters in turning AISI 1040 steel , 2013 .

[2]  Klaus Sattler,et al.  Handbook of Nanophysics : Nanoparticles and Quantum Dots , 2016 .

[3]  Albert J. Shih,et al.  Application of Nanofluids in Minimum Quantity Lubrication Grinding , 2008 .

[4]  A. Senthil Kumar,et al.  Evaluation of Minimal of Lubricant in End Milling , 2001 .

[5]  Deogratias Kibira,et al.  A Virtual Machining Model for Sustainability Analysis , 2010 .

[6]  M. RahmanM.,et al.  Optimization of Surface Roughness in End Milling on Mould Aluminium Alloys (AA6061-T6) Using Response Surface Method and Radian Basis Function Network , 2008 .

[7]  M. RahmanM.,et al.  Finite Element Analysis and Statistical Method to Determine Temperature Distribution on Cutting Tool in End-Milling , 2009 .

[8]  J. Srinivas,et al.  Prediction of Optimal Cutting States during Inward Turning: An Experimental Approach , 2010 .

[9]  R R Srikant,et al.  Applicability of cutting fluids with nanoparticle inclusion as coolants in machining , 2009 .

[10]  P. Chockalingam,et al.  Surface Roughness and Tool Wear Study on Milling of AISI 304 Stainless Steel Using Different Cooling Conditions , 2012 .

[11]  Rahman Saidur,et al.  A REVIEW ON APPLICATIONS AND CHALLENGES OF NANOFLUIDS , 2011 .

[12]  C. T. Nguyen,et al.  Heat transfer enhancement and pumping power in confined radial flows using nanoparticle suspensions (nanofluids) , 2011 .

[13]  P. Selvarani,et al.  SELECTION OF MACHINING PARAMETERS BASED ON THE ANALYSIS OF SURFACE ROUGHNESS AND FLANK WEAR IN FINISH TURNING AND FACING OF INCONEL 718 USING TAGUCHI TECHNIQUE , 2010 .

[14]  Sang Won Lee,et al.  Experimental characterization of micro-drilling process using nanofluid minimum quantity lubrication , 2011 .

[15]  O. K. Crosser,et al.  Thermal Conductivity of Heterogeneous Two-Component Systems , 1962 .

[16]  M. RahmanM.,et al.  Material Removal Rate and Surface Roughness on Grinding of Ductile Cast Iron Using Minimum Quantity Lubrication , 2015 .

[17]  Y. Kevin Chou,et al.  Characterizations of cutting tool flank wear-land contact , 2007 .

[18]  Pil-Ho Lee,et al.  Environmentally-Friendly Nano-fluid Minimum Quantity Lubrication (MQL) Meso-scale Grinding Process Using Nano-diamond Particles , 2010, 2010 International Conference on Manufacturing Automation.

[19]  Stefania Rizzuti,et al.  Evaluation of the Environmental Impact of different Lubrorefrigeration Conditions in Milling of γ-TiAl Alloy , 2011 .

[20]  Ying Liu,et al.  Preparation and tribological properties of dual-coated TiO 2 nanoparticles as water-based lubricant additives , 2014 .

[21]  M. RahmanM.,et al.  NEURAL NETWORK MODELING OF GRINDING PARAMETERS OF DUCTILE CAST IRON USING MINIMUM QUANTITY LUBRICATION , 2015 .

[22]  S. Tung,et al.  Tool life and wear mechanism of uncoated and coated milling inserts , 1999 .

[23]  P. V. Rao,et al.  Experimental investigation to study the effect of solid lubricants on cutting forces and surface quality in end milling , 2006 .

[24]  Álisson Rocha Machado,et al.  Application of cutting fluids in machining processes , 2001 .

[25]  Peter Krajnik,et al.  Nanofluids: Properties, Applications and Sustainability Aspects in Materials Processing Technologies , 2011 .

[26]  M. RahmanM.,et al.  Machining Performance Of Aluminum Alloy 6061-T6 On Surface Finish Using Minimum Quantity Lubrication , 2015 .

[27]  Che Hassan Che Haron,et al.  OPTIMIZATION OF MATERIAL REMOVAL RATE, SURFACE ROUGHNESS AND TOOL LIFE ON CONVENTIONAL DRY TURNING OF FCD700 , 2010 .

[28]  K. Kadirgama,et al.  Performance of Water-Based Zinc Oxide Nanoparticle Coolant during Abrasive Grinding of Ductile Cast Iron , 2014 .

[29]  Fumihiro Itoigawa,et al.  Effects and mechanisms in minimal quantity lubrication machining of an aluminum alloy , 2006 .

[30]  B. Blanpain,et al.  Strong static magnetic field processing of metallic materials: A review , 2012 .

[31]  Patrick Kwon,et al.  Effect of Nano-Enhanced Lubricant in Minimum Quantity Lubrication Balling Milling , 2011 .

[32]  M. Silva,et al.  Some observations on wear and damages in cemented carbide tools , 2006 .

[33]  Mohd Nizam Ab Rahman,et al.  MACHINABILITY OF FCD 500 DUCTILE CAST IRON USING COATED CARBIDE TOOL IN DRY MACHINING CONDITION , 2009 .

[34]  M. RahmanM.,et al.  Artificial neural network modeling of grinding of ductile cast iron using water based sio2 nanocoolant , 2014 .

[35]  B. K. Vinayagam,et al.  Nano surface generation of grinding process using carbon nano tubes , 2010 .

[36]  I. S. Jawahir,et al.  Sustainable manufacturing: Modeling and optimization challenges at the product, process and system levels , 2010 .