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Parametric Optimization of CNC Turning on LM25 Aluminum Alloy Using Taguchi Based Grey Relational Analysis


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DOI: https://doi.org/10.15866/ireme.v13i5.17410

Abstract


This paper presents a novel approach in parametric optimization of machining LM 25 aluminium alloy by Taguchi based grey relational analysis. The optimization of cutting speed (V), feed rate (F), depth of cut (D), and cutting fluid flow rate (R) is performed taking into account the surface roughness (Ra) and the material removal rate (MRR). Ahonol- 7 is the cutting fluid utilized for machining operation. The optimum machining parameters are determined based on the grey relational grade (GRG) values. A statistical technique comprising of orthogonal array and analysis of variance (ANOVA) is employed in order to find the significant contribution of parameters. A Confirmation test is conducted in order to validate the optimal machining parameters. From this analysis, it is predicted that cutting fluid flow rate is the most influential parameter that affects the turning of LM 25 Aluminum alloy. Cutting fluid flow rate influences R (47.70%) more, followed by feed rate F (35.94 %), depth of cut D (12.16%) and cutting speed V (3.02 %).
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Keywords


Optimization; Grey Relational Analysis; LM 25 Aluminum Alloy; Surface Roughness; Metal Removal Rate (MRR)

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References


Benardos, P. G., and G-C. Vosniakos. Predicting surface roughness in machining: a review, International journal of machine tools and manufacture 43, no. 8 (2003): 833-844.
https://doi.org/10.1016/s0890-6955(03)00059-2

Arbizu, I. Puertas, and CJ Luis Perez, Surface roughness prediction by factorial design of experiments in turning processes, Journal of Materials Processing Technology 143 (2003): 390-396.
https://doi.org/10.1016/s0924-0136(03)00407-2

Jayaraman, P. Multi-response optimization of machining parameters of turning AA6063 T6 aluminium alloy using grey relational analysis in Taguchi method, Procedia Engineering, 97 (2014): 197-204.
https://doi.org/10.1016/j.proeng.2014.12.242

Siddiquee, Arshad Noor, Zahid A. Khan, and Zulquernain Mallick, Grey relational analysis coupled with principal component analysis for optimisation design of the process parameters in in-feed centreless cylindrical grinding, The International Journal of Advanced Manufacturing Technology 46, no. 9-12 (2010): 983-992.
https://doi.org/10.1007/s00170-009-2159-8

Patole, P. B., and V. V. Kulkarni, Experimental investigation and optimization of cutting parameters with multi response characteristics in MQL turning of AISI 4340 using nano fluid, Cogent Engineering 4, no. 1 (2017): 1303956.
https://doi.org/10.1080/23311916.2017.1303956

Saha, A. Empirical modelling of machining parameters for turning operations using multiobjective Taguchi method, International Journal of Automotive and Mechanical Engineering 14 (2017): 4448-4461.
https://doi.org/10.15282/ijame.14.3.2017.5.0352

Ramnath, B. Vijaya, S. Sharavanan, and J. Jeykrishnan. Optimization of process parameters in drilling of fibre hybrid composite using Taguchi and grey relational analysis, In IOP Conference Series: Materials Science and Engineering, vol. 183, no. 1, p. 012003. IOP Publishing, 2017.
https://doi.org/10.1088/1757-899x/183/1/012003

Pillai, Jayakrishnan Unnikrishna, Ikshit Sanghrajka, Manikandakumar Shunmugavel, T. Muthuramalingam, Moshe Goldberg, and Guy Littlefair, Optimisation of multiple response characteristics on end milling of aluminium alloy using Taguchi-Grey relational approach, Measurement, 124 (2018): 291-298.
https://doi.org/10.1016/j.measurement.2018.04.052

Mvola, B., Adaptive Gas Metal Arc Welding Control and Optimization of Welding Parameters Output: Influence on Welded Joints, (2016) International Review of Mechanical Engineering (IREME), 10 (2), pp. 67-72.
https://doi.org/10.15866/ireme.v10i2.7471

Manikandan, N., Kumanan, S., & Sathiyanarayanan, C. (2017). Multiple performance optimization of electrochemical drilling of Inconel 625 using Taguchi based Grey Relational Analysis, Engineering Science and Technology, an International Journal, 20(2), 662-671.
https://doi.org/10.1016/j.jestch.2016.12.002

Singh, Vikram, Rakesh Bhandari, and Vinod Kumar Yadav, An experimental investigation on machining parameters of AISI D2 steel using WEDM, The International Journal of Advanced Manufacturing Technology 93, no. 1-4 (2017): 203-214.
https://doi.org/10.1007/s00170-016-8681-6

Yerrawar, R., Arakerimath, R., Taguchi Based Grey Relational Analysis Methodology for Semi Active Suspension System Using MR Damper, (2017) International Review of Mechanical Engineering (IREME), 11 (9), pp. 666-672.
https://doi.org/10.15866/ireme.v11i9.13393

Gupta, Meenu, and Surinder Kumar, Multi-objective optimization of cutting parameters in turning using grey relational analysism International Journal of Industrial Engineering Computations 4, no. 4 (2013): 547-558.
https://doi.org/10.5267/j.ijiec.2013.06.001

Lin, C. L., Use of the Taguchi method and grey relational analysis to optimize turning operations with multiple performance characteristic, Materials and manufacturing processes 19, no. 2 (2004): 209-220.
https://doi.org/10.1081/amp-120029852

Rajesh, S., D. Devaraj, R. Sudhakara Pandian, and S. Rajakarunakaran, Multi-response optimization of machining parameters on red mud-based aluminum metal matrix composites in turning process, The International Journal of Advanced Manufacturing Technology 67, no. 1-4 (2013): 811-821.
https://doi.org/10.1007/s00170-012-4525-1

Hassan, Kamal, Anish Kumar, and M. P. Garg, "Experimental investigation of Material removal rate in CNC turning using Taguchi method, International Journal of Engineering Research and Applications 2, no. 2 (2012): 1581-1590.

Ribeiro, João, Hernâni Lopes, Luis Queijo, and Daniel Figueiredo, Optimization of cutting parameters to minimize the surface roughness in the end milling process using the Taguchi method, Periodica Polytechnica Mechanical Engineering 61, no. 1 (2017): 30-35.
https://doi.org/10.3311/ppme.9114

Basmaci, G., and M. Ay., Optimization of Cutting Parameters, Condition and Geometry in Turning AISI 316L Stainless Steel Using the Grey-Based Taguchi Method, Acta Physica Polonica A 131, no. 3 (2017): 354-358.
https://doi.org/10.12693/aphyspola.131.354

Palanikumar, K., L. Karunamoorthy, and R. Karthikeyan, Multiple performance optimization of machining parameters on the machining of GFRP composites using carbide (K10) tool, Materials and Manufacturing Processes 21, no. 8 (2006): 846-852.
https://doi.org/10.1080/03602550600728166

Sharma, Pankaj, and Kamaljeet Bhambri. Multi-response optimization by experimental investigation of machining parameters in CNC turning by Taguchi based grey relational analysis, International Journal of Engineering Research and Applications 2, no. 5 (2012): 1594-1602.

Shivade, Anand S., Shivraj Bhagat, Suraj Jagdale, Amit Nikam, and Pramod Londhe, Optimization of Machining Parameters for Turning using Taguchi Approach, International journal of recent technology and engineering 3, no. 1 (2014): 145-149.

Nayak, Shreemoy Kumar, Jatin Kumar Patro, Shailesh Dewangan, and Soumya Gangopadhyay, Multi-objective optimization of machining parameters during dry turning of AISI 304 austenitic stainless steel using grey relational analysis, Procedia Materials Science 6 (2014): 701-708.
https://doi.org/10.1016/j.mspro.2014.07.086

Ramanujam, Radhakrishnan, Nambi Muthukrishnan, and Ramasamy Raju, Optimization of cutting parameters for turning Al-SiC (10p) MMC using ANOVA and grey relational analysis International Journal of Precision Engineering and Manufacturing 12, no. 4 (2011): 651-656.
https://doi.org/10.1007/s12541-011-0084-x

Saha, Abhijit, and N. Mandal, Optimization of machining parameters of turning operations based on multi performance criteria, International Journal of Industrial Engineering Computations 4, no. 1 (2013): 51-60
https://doi.org/10.5267/j.ijiec.2012.11.004

Rogov, Vladimir Aleksandrovich, and Ghorbani Siamak. Optimization of surface roughness and vibration in turning of aluminum alloy AA2024 using taguchi technique, International Journal of Mechanical and Mechatronics Engineering 7, no. 11 (2013): 2330-2339.

Nayak, I., and J. Rana. Selection of a suitable multiresponse optimization technique for turning operation, Decision Science Letters 5, no. 1 (2016): 129-142.
https://doi.org/10.5267/j.dsl.2015.7.003

Varghese, Vinay, M. R. Ramesh, and D. Chakradhar. Experimental investigation and optimization of machining parameters for sustainable machining, Materials and Manufacturing Processes 33, no. 16 (2018): 1782-1792.
https://doi.org/10.1080/10426914.2018.1476760


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