EXPERIMENTAL ANALYSIS AND OPTIMIZATION OF THE CONTROLLABLE PARAMETERS IN TURNING OF EN AW-2011 ALLOY; DRY MACHINING AND ALTERNATIVE COOLING TECHNIQUES

Sonja Jozić, Ivana Dumanić, Dražen Bajić

DOI Number
https://doi.org/10.22190/FUME191024009J
First page
013
Last page
029

Abstract


The latest trends in machining research show that great efforts are being made to understand the impact of different cooling and lubrication techniques as well as cutting parameters on machining performances. This paper presents the investigation results of different cutting parameters and different cutting environments such as dry machining, minimum quantity lubrication (MQL) and minimum quantity lubrication with compressed cold air (MQL+CCA) on average surface roughness, cutting force and material removal rate. The experiments were designed based on three input parameters and three different cutting environments when turning of EN AW-2011 alloy. Taguchi-based grey relational analysis was used to identify the optimal process parameters by which minimum values of surface roughness, minimum value of cutting force and maximum value of material removal rate will be achieved. The results showed that minimum quantity lubrication in the stream of compressed cold air, in comparison to dry and minimum quantity lubrication machining, gives the best machining performances. Therefore, the use of MQL + CCA method, which reduces the amount of lubricant may represent in the described extent of turning operations an alternative to turning processes most often carried out by wet method that causes considerable costs for purchasing, maintaining and using cutting fluids.


Keywords

Turning, Dry Machining, Minimum Quantity of Lubrication, Compressed Cold Air Cooling, Taguchi Design, Grey Relational Analysis

Full Text:

PDF

References


Kant, G., Sangwan, K.S., 2015, Predictive modelling and optimization of machining parameters to minimize surface roughness using artificial neural network coupled with genetic algorithm, Procedia CIRP 31, pp. 453-458.

Adler, D.P., Hii, W.W-S., Michalek, D.J., Sutherland, J.W., 2006, Examining the role of cutting fluids in machining and efforts to address associated environmental/health concerns, Machining Science and Technology, 10(1), pp. 23-58.

Hong, S.Y., Broomer, M., 2000, Economical and ecological cryogenic machining of AISI 304 austenitic stainless steel, Clean Products and Processes, 2, pp. 157–166.

Goindi, G., Sarkar, P., 2017, Dry Machining: A Step towards Sustainable Machining - Challenges and Future Directions, Journal of Cleaner Production 165, DOI: 10.1016/j.jclepro.2017.07.235

Lawal, S.A., Choudhury, I.A., Nukman, Y., 2012, A Critical Assessment of Lubrication Techniques in Machining Processes: A Case for Minimum Quantity Lubrication Using Vegetable Oil-Based Lubricant, Journal of Cleaner Production, doi: 10.1016/j.jclepro.2012.10.016.

Dhar, N.R., Islam, M.W., Islam, S., Mithu, M.A.H., 2006, The influence of minimum quantity of lubrication (MQL) on cutting temperature, chip and dimensional accuracy in turning AISI-1040 steel, Journal of Materials Processing Technology 171(1), pp. 93-99.

Priarone, P.C., Rizzuti, S., Rotella, G., Settineri, L., 2012, Tool wear and surface quality in milling of a gamma-TiAl intermetallic, The International Journal of Advanced Manufacturing Technology, 61, pp. 25-33.

Jianxin, D., Tongkun, C., Lili, L., 2005, Self-lubricating behaviours of Al2O3/TiB2 ceramic tools in dry high-speed machining of hardened steel, Journal of the European Ceramic Society 25, pp. 1073–1079.

Sharma, V.S., Dogra, M., Suri, N.M., 2009, Cooling techniques for improved productivity in turning, International Journal of Machine Tools and Manufacture, 49(6), pp. 435-453.

Maruda, R.W., Legutko, S., Krolczyk, G.M., 2014, Effect of minimum quantity cooling lubrication (MQCL) on chip morphology and surface roughness in turning low carbon steels, Applied Mechanics and Materials, 657, pp.38-42.

Maruda, R.W., Legutko, S., Krolczyk, G.M., Raos, P., 2015, Influence of cooling conditions on the machining process under MQCL and MQL conditions, Tehnički vjesnik, 22(4), pp. 965-970.

Dixit, U.S., Sarma, D.K., Davim, J.P., 2012, Environmentally friendly machining. Springer Science & Business Media, LLC, New York.

Nouioua, M., Yallese, M.A., Khettabi, R., Chabbi, A., Mabrouki, T., Girardin, F., 2017, Optimization of Machining Process During Turning of X210Cr12 Steel Under MQL Cooling as a Key Factor in Clean Production. International Conference Design and Modeling of Mechanical Systems, DOI: 10.1007/978-3-319-66697-6_83.

Pervaiz, S., Deiab, I., Rashid, A., Nicolescu, M., 2017, Minimal quantity cooling lubrication in turning of Ti6Al4V: influence on surface roughness, cutting force and tool wear. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 231(9), pp. 1542-1558.

Pervaiz, S., Rashid, A., Deiab, I., Nicolescu, C.M., 2016, An experimental investigation on effect of minimum quantity cooling lubrication (MQCL) in machining titanium alloy (Ti6Al4V), The International Journal of Advanced Manufacturing Technology, 87(5-8), pp. 1371-1386.

Yuan. S.M., Yan, L.T., Liu, W.D., Liu, Q., 2011, Effects of compressed cold air temperature on cryogenic machining of Ti–6Al–4V alloy, Journal of Materials Processing Technology, 211(3), pp. 356-362.

Singh, G., Sharma, V.S., 2017, Analysing machining parameters for commercially pure titanium (Grade 2), cooled using minimum quantity lubrication assisted by a Ranque-Hilsch vortex tube, International Journal of Advanced Manufacturing Technology, 88, pp. 2921–2928.

Diyaley, S., Chakraborty, S., 2019, Optimization of multi-pass face milling parameters using metaheuristic algorithms, Facta Universitatis-Series Mechanical Engineering, 17(3), pp. 365 – 383.

Gopal, P.M., Prakash, K.S., 2018, Minimization of cutting force, temperature and surface roughness through GRA, TOPSIS and Taguchi techniques in end milling of Mg hybrid MMC, Measurement, 116, pp. 178–192.

Fratila, D., Caizar, C., 2011, Application of Taguchi method to selection of optimal lubrication and cutting conditions in face milling of AlMg3, Journal of Cleaner Production, 19(6-7), pp. 640-645.

Yan, J., Li, L., 2013, Multi-objective optimization of milling parameters–the trade-offs between energy, production rate and cutting quality, Journal of Cleaner Production, 52, pp. 462-471.

Lin, C.L., 2004, Use of the Taguchi method and grey relational analysis to optimize turning operations with multiple performance characteristics, Materials and manufacturing processes, 19(2), pp. 209-220.

Tripathy, S., Tripathy, D.K., 2017, Multi-response optimization of machining process parameters for powder mixed electro-discharge machining of H-11 die steel using grey relational analysis and topsis. Machining science and technology, 21(3), pp. 362-384.

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, Advanced Manufacturing, 7, pp. 142-154.

Mia, M., Khan, M.A., Dhar, N.R., 2017, Study of surface roughness and cutting forces using ANN, RSM, and ANOVA in turning of Ti-6Al-4V under cryogenic jets applied at flank and rake faces of coated WC tool, International Journal of Advanced Manufacturing Technology, 93(1–4), pp. 975–991.

Mia, M., Khan, M.A., Rahman, S.S., Dhar, N.R., 2017, Mono-objective and multi-objective optimization of performance parameters in high pressure coolant assisted turning of Ti-6Al-4V, International Journal of Advanced Manufacturing Technology, 90(1–4), pp. 109–118.

Aman, A., Hari, S., Pradeep, K., Manmohan, S., 2008, Optimizing power consumption for CNC turned parts using response surface methodology and Taguchi's technique—A comparative analysis, Journal of Materials Processing Technology, Volume 200(1) – May 8, 2008

Boswell, B., Islam, M.N., Davies, I.J., Ginting, Y.R., Ong, A.K., 2017, A review identifying the effectiveness of minimum quantity lubrication (MQL) during conventional machining, International Journal of Advanced Manufacturing Technology, 92, pp. 321–340.




DOI: https://doi.org/10.22190/FUME191024009J

Refbacks

  • There are currently no refbacks.


ISSN: 0354-2025 (Print)

ISSN: 2335-0164 (Online)

COBISS.SR-ID 98732551

ZDB-ID: 2766459-4