Multi-objective Optimization of Turning of Titanium Alloy Under Minimum Quantity Lubrication

Document Type : Original Manuscript

Authors

1 Department of Mechanical Engineering, Vishwakarma Institute of Information Technology, India

2 Department of Mechanical Engineering, SRM Institute of Science and Technology, Chennai, India.

3 Department of Mechanical Engineering, Vishwakarma Institute of Information Technology, India.

Abstract

In the present study, the machining performance of titanium grade-1 alloy is evaluated in terms of resultant cutting force, machined surface roughness, and material removal rate (MRR) through a multi-objective optimization approach. Turning experiments were performed with CVD-coated TiCN-Al2O3 carbide inserts using vegetable oil-based nanofluid under minimum quantity lubrication. The nanofluid was prepared using coconut oil as a base fluid mixed with boron nitride (hBN) nanoparticles. Experiments were performed by varying the cutting speed, feed, depth of cut, and nanoparticles concentration in a base fluid. The Desirability Function Approach (DFA), a Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Grey Relational Analysis (GRA), and Non-dominated Sorting Genetic Algorithm (NSGA-II) are used to optimize the machining performance. The optimized solutions from different optimization techniques are observed in better agreement. The results show optimum performance at the higher cutting speed, higher depth of cut, lower feed, and lower concentration of nanoparticles. Lowest values for resultant force and surface roughness of 387 N and 0.47 µm, respectively, and maximum MRR of 9375 mm3/min could be obtained using the cutting speed, feed, depth of cut, and nanoparticles concentration of 125 m/min, 0.1 mm/rev, 0.75 mm, and 0.3%, respectively. However, little compromising the surface roughness to a higher value of 0.83 µm with almost the same resultant force, the higher MRR of 15000 mm3/min could be obtained using higher cutting parameters. It has been observed that the resultant force and surface roughness are significantly affected by the depth of cut and feed, respectively. However, the concentration of nanoparticles has been observed to have a lower prominent effect on the surface roughness and resultant force.

Graphical Abstract

Multi-objective Optimization of Turning of Titanium Alloy Under Minimum Quantity Lubrication

Highlights

  • The coconut oil mixed with boron nitride nanoparticles used under MQL turning of Ti alloy
  • Depth of cut, nanoparticles concentration significantly affects cutting force in titanium turning
  • Feed significantly and nanoparticles concentration negligibly affect surface roughness
  • NSGA-II followed by desirability function approach are better for multi-objective optimization

Keywords


Aitken, R. J., Chaudhry, M. Q., Boxall, A. B. A., & Hull, M. (2006). Manufacture and use of nanomaterials: current status in the UK and global trends. Occupational medicine, 56(5), 300-306.
Anandan, V., Babu, M. N., Muthukrishnan, N., & Babu, M. D. (2020). Performance of silver nanofluids with minimum quantity lubrication in turning on titanium: a phase to green manufacturing. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 42(4), 1-15.
Asadi, A., Saidi-Mehrabad, M., & Fathi Aghdam, F. (2019). A Two-Dimensional Warranty Model With Consideration Of Customer And Manufacturer Objectives Solved With Non-Dominated Sorting Genetic Algorithm. Journal Of Optimization In Industrial Engineering, 12(1), 15-22.
Boyer, R. R., & Briggs, R. D. (2005). The use of β titanium alloys in the aerospace industry. Journal of Materials Engineering and Performance, 14(6), 681-685.
Chinchanikar, S., Kore, S. S., & Hujare, P. (2021). A review on nanofluids in minimum quantity lubrication machining. Journal of Manufacturing Processes, 68, 56-70.
Chinchanikar, S., Bawangaonwala, H. M., Bokade, S., & Garode, S. (2020). Investigations on the Machining Performance using Solid Lubricant Mixed with Varying Proportions in Vegetable Oil during Hard Turning. In IOP Conference Series: Materials Science and Engineering (Vol. 810, No. 1, p. 012044). IOP Publishing.
Chinchanikar, S., & Choudhury, S. K. (2015). Machining of hardened steel—experimental investigations, performance modeling and cooling techniques: a review. International Journal of Machine Tools and Manufacture, 89, 95-109.
Chinchanikar, S., & Choudhury, S. K. (2013). Effect of work material hardness and cutting parameters on performance of coated carbide tool when turning hardened steel: An optimization approach. Measurement, 46(4), 1572-1584.
Das, S. K., Choi, S. U., & Patel, H. E. (2006). Heat transfer in nanofluids—a review. Heat transfer engineering, 27(10), 3-19.
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. A. M. T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE transactions on evolutionary computation, 6(2), 182-197.
Dhar, N. R., Ahmed, M. T., & Islam, S. (2007). An experimental investigation on effect of minimum quantity lubrication in machining AISI 1040 steel. International Journal of Machine Tools and Manufacture, 47(5), 748-753.
Dhar, N. R., Kamruzzaman, M., & Ahmed, M. (2006). Effect of minimum quantity lubrication (MQL) on tool wear and surface roughness in turning AISI-4340 steel. Journal of materials processing technology, 172(2), 299-304.
Gaurav, G., Sharma, A., Dangayach, G. S., & Meena, M. L. (2020). Assessment of jojoba as a pure and nano-fluid base oil in minimum quantity lubrication (MQL) hard-turning of Ti–6Al–4V: A step towards sustainable machining. Journal of Cleaner Production, 272, 122553.
Gupta, M. K., Sood, P. K., & Sharma, V. S. (2016). Optimization of machining parameters and cutting fluids during nano-fluid based minimum quantity lubrication turning of titanium alloy by using evolutionary techniques. Journal of Cleaner Production, 135, 1276-1288.
Hegab, H., Umer, U., Deiab, I., & Kishawy, H. (2018). Performance evaluation of Ti-6Al-4V machining using nano-cutting fluids under minimum quantity lubrication. International Journal of Advanced Manufacturing Technology, 95, 4229–4241.
Jamil, M., He, N., Li, L., & Khan, A. M. (2020). Clean manufacturing of Ti-6Al-4V under CO2-snow and hybrid nanofluids. Procedia Manufacturing, 48, 131-140.
Jozić, S., Bajić, D., & Celent, L. (2015). Application of compressed cold air cooling: achieving multiple performance characteristics in end milling process. Journal of Cleaner Production, 100, 325-332.
Kalyon, A., Günay, M., & Özyürek, D. (2018). Application of grey relational analysis based on Taguchi method for optimizing machining parameters in hard turning of high chrome cast iron. Advances in Manufacturing, 6(4), 419-429.
Kang, M. C., Kim, K. H., Shin, S. H., Jang, S. H., Park, J. H., & Kim, C. (2008). Effect of the minimum quantity lubrication in high-speed end-milling of AISI D2 cold-worked die steel (62 HRC) by coated carbide tools. Surface and Coatings Technology, 202(22-23), 5621-5624.
Katta, S., & Chaitanya, R. S. (2018). Experimental Investigations of Graphene Nanoparticle-Based Cutting Fluid during Turning of Titanium Alloy (Grade 5) with Minimum Quantity Lubrication. Journal of Advanced Research in Manufacturing, Material Science & Metallurgical Engineering, 5(1&2), 22-30.
Kishawy, H. A., Dumitrescu, M., Ng, E. G., & Elbestawi, M. A. (2005). Effect of coolant strategy on tool performance, chip morphology and surface quality during high-speed machining of A356 aluminum alloy. International Journal of Machine Tools and Manufacture, 45(2), 219-227.
Khakzar Bafruei, M., Khatibi, S., & Rahmani, M. (2018). A Bi-Objective Airport Gate Scheduling with Controllable Processing Times Using Harmony Search and NSGA-II Algorithms. Journal of Optimization in Industrial Engineering, 11(1), 77-90.
Kosaraju, S., & Anne, V. G. (2013). Optimal machining conditions for turning Ti-6Al-4V using response surface methodology. Advances in Manufacturing, 1(4), 329-339.
Krishna, P. V., Srikant, R. R., & Rao, D. N. (2010). Experimental investigation on the performance of nanoboric acid suspensions in SAE-40 and coconut oil during turning of AISI 1040 steel. International Journal of machine Tools and manufacture, 50(10), 911-916.
Kumar, R., Sahoo, A. K., Mishra, P. C., & Das, R. K. (2018). Comparative study on machinability improvement in hard turning using coated and uncoated carbide inserts: part II modeling, multi-response optimization, tool life, and economic aspects. Advances in Manufacturing, 6(2), 155-175.
Kumar, T. A., Pradyumna, G., & Jahar, S. (2012). Investigation of thermal conductivity and viscosity of nanofluids. Journal of environmental research and development, 7(2).
Kumar, C. R. V., & Ramamoorthy, B. (2007). Performance of coated tools during hard turning under minimum fluid application. Journal of Materials Processing Technology, 185(1-3), 210-216.
Leppert, T. (2011). Effect of cooling and lubrication conditions on surface topography and turning process of C45 steel. International Journal of Machine Tools and Manufacture, 51(2), 120-126.
Li, N., Chen, Y. J., & Kong, D. D. (2019). Multi-response optimization of Ti-6Al-4V turning operations using Taguchi-based grey relational analysis coupled with kernel principal component analysis. Advances in Manufacturing, 7(2), 142-154.
Lin, J. L., & Tarng, Y. S. (1998). Optimization of the multi-response process by the Taguchi method with grey relational analysis. Journal of Grey system, 4(4), 355-370.
Liu, Z., An, Q., Xu, J., Chen, M., & Han, S. (2013). Wear performance of (nc-AlTiN)/(a-Si3N4) coating and (nc-AlCrN)/(a-Si3N4) coating in high-speed machining of titanium alloys under dry and minimum quantity lubrication (MQL) conditions. Wear, 305(1-2), 249-259.
Maadanpour Safari, F., Etebari, F., & Pourghader Chobar, A. (2021). Modelling and optimization of a tri-objective Transportation-Location-Routing Problem considering route reliability: using MOGWO, MOPSO, MOWCA and NSGA-II. Journal of Optimization in Industrial Engineering, 14(2), 99-114.
Maruda, R. W., Krolczyk, G. M., Michalski, M., Nieslony, P., & Wojciechowski, S. (2017). Structural and microhardness changes after turning of the AISI 1045 steel for minimum quantity cooling lubrication. Journal of Materials Engineering and Performance, 26(1), 431-438.
Rahmati, B., Sarhan, A. A., & Sayuti, M. (2014). Investigating the optimum molybdenum disulfide (MoS 2) nanolubrication parameters in CNC milling of AL6061-T6 alloy. The International Journal of Advanced Manufacturing Technology, 70(5-8), 1143-1155.
Rao, R. V. (2011). Overview. In Advanced Modeling and Optimization of Manufacturing Processes (pp. 1-54). Springer, London.
Sharma, A. K., Katiyar, J. K., Bhaumik, S., & Roy, S. (2019). Influence of alumina/MWCNT hybrid nanoparticle additives on tribological properties of lubricants in turning operations. Friction, 7(2), 6.
Sharma, A. K., Singh, R. K., Dixit, A. R., & Tiwari, A. K. (2017). Novel uses of alumina-MoS2 hybrid nanoparticle enriched cutting fluid in hard turning of AISI 304 steel. Journal of Manufacturing Processes, 30, 467-482.
Sharma, A. K., Tiwari, A. K., & Dixit, A. R. (2015). Progress of nanofluid application in machining: a review. Materials and Manufacturing Processes, 30(7), 813-828.
Singh, V., Sharma, A. K., Sahu, R. K., & Katiyar, J. K. (2021). Novel application of graphite-talc hybrid nanoparticle enriched cutting fluid in turning operation. Journal of Manufacturing Processes, 62, 378-387.
Varote, N., & Joshi, S. S. (2017). Microstructural analysis of machined surface integrity in drilling a titanium alloy. Journal of Materials Engineering and Performance, 26(9), 4391-4401.