Abstract
Metalworking fluids (MWF’s) are frequently used for cooling and lubrication during machining processes in manufacturing industries. MWF’s such as soluble straight oils, synthetic oils, solid lubricants, bio lubricants contain a mix of water and mineral oil with some percentage of vegetable oils and petroleum. These MWF’s are hazardous for the environment and for human health. After using, the lubricants are disposed into the environment by burning or by dumping on the ground or in the sea water. Burning the lubricant creates pollution and airborne disease. To avoid these harmful effects of the lubricants sustainable machining technique is implemented in machining processes. In the present study, liquid nitrogen (green coolant) is used as a sustainable machining technique for cooling and lubrication. Finite element modeling is used to simulate the micro-end milling at different conditions of the workpiece (cryogenic plus preheated and cryogenic). The analysis of chip morphology and cutting forces measurement were done by applying these conditions. The predicted model is validated with the experimental results. It was observed that cryogenic with preheated workpiece (473 K) is the optimum condition with the application of green coolant. This study will clarify the behavior of cryogenic on the machining conditions and will solve the environmental problems.
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References
Li, K., & Liang, S. (2007). Performance profiling of minimum quantity lubrication in machining. International Journal of Advanced Manufacturing Technology, 35, 226–233.
Yoon, H.-S., Kim, M.-S., Jang, K.-H., & Ahn, S.-H. (2016). Future perspectives of sustainable manufacturing and applications based on research databases. International Journal of Precision Engineering and Manufacturing, 17(9), 1249–1263.
Kim, H. J., Seo, K. J., Kang, K. H., & Kim, D. E. (2016). Nano-lubrication: A review. International Journal of Precision Engineering and Manufacturing, 17(6), 829–841.
Park, K. H., Yang, G. D., & Lee, D. Y. (2015). Tool wear analysis on coated and uncoated carbide tools in Inconel machining. International Journal of Precision Engineering and Manufacturing, 16(7), 1639–1645.
Pusavec, F., Krajnik, P., & Kopac, J. (2010). Transitioning to sustainable production—Part I: application on machining technologies. Journal of Cleaner Production, 18(2), 174–184.
Park, K. H., Suhaimi, M. A., Yang, G. D., et al. (2017). Milling of titanium alloy with cryogenic cooling and minimum quantity lubrication (MQL). International Journal of Precision Engineering and Manufacturing, 18(1), 5–14.
Jeon, Y., Park, H. W., & Lee, C. M. (2013). Current research trends in external energy assisted machining. International Journal of Precision Engineering and Manufacturing, 14(2), 337–342.
Choi, H. J., Park, C. W., Kang, I. S., Kim, J. S., & Choi, S. D. (2016). Material model application considering strain softening for cutting simulation of Ti-6Al-4V alloy and its experimental validation. International Journal of Precision Engineering and Manufacturing, 17(12), 1651–1658.
Zhang, S., Li, J. F., & Wang, Y. W. (2012). Tool life and cutting forces in end milling Inconel 718 under dry and minimum quantity cooling lubrication cutting conditions. Journal of Cleaner Production, 32, 81–87.
Ning, J., & Liang, S. (2018). Prediction of temperature distribution in orthogonal machining based on the mechanics of the cutting process using a constitutive model. Journal of Manufacturing and Materials Processing, 2(2), 37.
Aydın, M. (2016). Cutting temperature analysis considering the improved Oxley’s predictive machining theory. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 38(8), 2435–2448.
Ning, J., & Liang, S. (2019). Predictive modeling of machining temperatures with force-temperature correlation using cutting mechanics and constitutive relation. Materials (Basel), 12(2), 284.
Ning, J., & Liang, S. (2018). Evaluation of an analytical model in the prediction of machining temperature of AISI 1045 steel and AISI 4340 steel. Journal of Manufacturing and Materials Processing, 2(4), 74.
Ning, J., Nguyen, V., & Liang, S. (2018). Analytical modeling of machining forces of ultra-fine-grained titanium. International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-018-2889-6.
Lalwani, D. I., Mehta, N. K., & Jain, P. K. (2009). Extension of Oxley’s predictive machining theory for Johnson and Cook flow stress model. Journal of Materials Processing Technology, 209(12–13), 5305–5312.
Jain, A., Khanna, N., & Bajpai, V. (2018). FE simulation of machining of Ti-54M titanium alloy for industry relevant outcomes. Measurement, 129, 268–276.
Davoudinejad, A., Tosello, G., & Annoni, M. (2017). Influence of the worn tool affected by built-up edge (BUE) on micro end-milling process performance: A 3D finite element modeling investigation. International Journal of Precision Engineering and Manufacturing, 18(10), 1321–1332.
Singh, K. K., Singh, R., & Kartik, V. (2015). Comparative study of Chatter detection methods for high-speed micromilling of Ti6Al4V. Procedia Manufacturing, 1, 593–606.
Singh, K. K., Kartik, V., & Singh, R. (2015). Modeling dynamic stability in high-speed micromilling of Ti-6Al-4V via velocity and chip load dependent cutting coefficients. International Journal of Machine Tools and Manufacture, 96, 56–66.
Zamani, H., Hermani, J., Sonderegger, B., & Sommitsch, C. (2013). 3D simulation and process optimization of laser assisted milling of Ti6Al4V. Procedia CIRP, 8, 75–80.
Ko, D. H., Ko, D. C., Lim, H. J., Lee, J. M., & Kim, B. M. (2013). FE-simulation coupled with CFD analysis for prediction of residual stresses relieved by cryogenic heat treatment of Al6061 tube. International Journal of Precision Engineering and Manufacturing, 14(8), 1301–1309.
Wu, H. B., & Zhang, S. J. (2014). 3D FEM simulation of milling process for titanium alloy Ti6Al4V. International Journal of Advanced Manufacturing Technology, 71(5–8), 1319–1326.
Johnson, G. R., & Cook, W. H. (1983). A constitutive model and data for metals subjected to large strains, high strain rates and high temperatures. In 7th International symposium ballistics (pp. 541–547).
Özel, T., & Zeren, E. (2004). Determination of work material flow stress and friction for FEA of machining using orthogonal cutting tests. Journal of Materials Processing Technology, 153–154, 1019–1025.
Lesuer, D. (1991). Experimental investigations of material models for Ti-6AI-4V and 2024-T3 aluminum. In Final Report, UCRL-ID-134691, US Department of Transportation, Federal Aviation Administration.
Ning, J., & Liang, S. (2018). Model-driven determination of Johnson–Cook material constants using temperature and force measurements. International Journal of Advanced Manufacturing Technology, 97(1–4), 1053–1106.
Agmell, M., Ahadi, A., & Ståhl, J. E. (2014). Identification of plasticity constants from orthogonal cutting and inverse analysis. Mechanics of Materials, 77, 43–51.
Ning, J., Nguyen, V., Huang, Y., et al. (2018). Inverse determination of Johnson–Cook model constants of ultra-fine-grained titanium based on chip formation model and iterative gradient search. International Journal of Advanced Manufacturing Technology, 99(5–8), 1131–1140.
Bajpai, V., Lee, I., & Park, H. W. (2014). Finite element modeling of three-dimensional milling process of Ti6Al4V. Materials and Manufacturing Processes, 29, 564–571.
Zhang, W. J., Reddy, B. V., & Deevi, S. C. (2001). Physical properties of TiAl-base alloys. Scripta Material, 45(6), 645–651.
Rahim, E. A., Ibrahim, M. R., Rahim, A. A., Aziz, S., & Mohid, Z. (2015). Experimental investigation of minimum quantity lubrication (MQL) as a sustainable cooling technique. Procedia CIRP, 26, 351–354.
Komanduri, R., & Von Turkovich, B. F. (1981). New observations on the mechanism when machining titanium alloys of chip formation. Wear, 69, 179–188.
Lee, I., Bajpai, V., Moon, S., Jungwon, B., Youngsoo, L., & Park, H. W. (2015). Tool life improvement in cryogenic cooled milling of the preheated Ti-6Al-4V. International Journal of Advanced Manufacturing Technology, 79, 665–673.
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Jain, A., Kumar, S., Bajpai, V. et al. Replacement of Hazard Lubricants by Green Coolant in Machining of Ti6Al4V: A 3D FEM Approach. Int. J. Precis. Eng. Manuf. 20, 1027–1035 (2019). https://doi.org/10.1007/s12541-019-00111-2
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DOI: https://doi.org/10.1007/s12541-019-00111-2