Abstract

Keyword: Machining parameters optimization, modified Taguchi method, surface roughness (RA), material removal rate (MRR), Al6351 alloy machining, multi-objective optimization

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Refrences:

1. H. S. Ram, M. Uthayakumar, S. S. Kumar, S. T. Kumaran, B. Azzopardi, and K. Korniejenko,
Prediction of Kerf Width and Surface Roughness of Al6351 Based Composite in Wire-Cut Electric
Discharge Machining Using Mathematical Modelling, Materials 2022, Vol. 15, Page 1102 15, 1102
(2022).
2. A. A. Premnath, T. Alwarsamy, and T. Rajmohan, Experimental Investigation and Optimization of
Process Parameters in Milling of Hybrid Metal Matrix Composites, Materials and Manufacturing
Processes 27, 1035 (2012).
3. T. Sathish, N. Sabarirajan, and S. Karthick, Machining parameters optimization of Aluminium
Alloy 6063 with reinforcement of SiC composites, Mater Today Proc 33, 2559 (2020).
4. Ö. Seçgin and M. Z. Sogut, Surface roughness optimization in milling operation for aluminum alloy
(Al 6061-T6) in aviation manufacturing elements, Aircraft Engineering and Aerospace Technology
93, 1367 (2021).
5. P. Jayaraman, L. Mahesh Kumar, and V. Jayaseelan, Multi-response Optimization of Cutting
Parameters During End-milling of AA6101 T6 Aluminium Alloy Using Grey Relational Analysis,
International Journal of Applied Engineering Research 10, 4275 (2015).
6. V. V. N. Sarath and N. Tamiloli, Optimization of multiple quality characteristics for end milling
under dry cutting environment using desirability function, J Phys Conf Ser 2070, 012218 (2021).
7. R. Sharma, K. Sharma, D. Singh, K. Mausam, and R. P. Singh, Investigation of Optimum Process
Parameter on CNC Turning for Aluminium Alloy AA6262 Using Grey Relational Analysis, Lecture
Notes in Mechanical Engineering 611 (2021).
8. N. TAMILOLI, J. VENKATESAN, T. KUMAR, A. ASHWIN, and Z. KALITCHIN, MILLING
PARAMETERS ON AA-6082-T6 ALLOY USING GRAY RELATIONAL ANALYSIS,
REGRESSION, ANN, AND GA MODELS, Journal of the Balkan Tribological Association 28, 233
(2022).
9. M. Manoharan, A. Kulandaivel, A. Arunagiri, M. R. A. Refaai, S. Yishak, and G. Buddharsamy,
Statistical Modelling to Study the Implications of Coated Tools for Machining AA 2014 Using
Grey Taguchi-Based Response Surface Methodology, Advances in Materials Science and
Engineering 2021, 6843276 (2021).
10. Z. Xing, H. Dai, J. Zhang, and Y. Li, Evaluation and Improvement of Greenness for Milling AL6061
Alloy through Life Cycle Assessment and Grey Relational Analysis, Materials 2022, Vol. 15, Page
8231 15, 8231 (2022).
11. J. Unnikrishna Pillai, I. Sanghrajka, M. Shunmugavel, T. Muthuramalingam, M. Goldberg, and G.
Littlefair, Optimisation of multiple response characteristics on end milling of aluminium alloy using
Taguchi-Grey relational approach, Measurement 124, 291 (2018).
12. S. Li, J. Sui, F. Ding, S. Wu, W. Chen, and C. Wang, Optimization of Milling Aluminum Alloy
6061-T6 using Modified Johnson-Cook Model, Simul Model Pract Theory 111, 102330 (2021).
13. CHEN Liang-ji and WEI Zi-sen, Multi-objective Synchronous Optimization Method for Milling
Parameters and Tool Geometric Parameters of 7075-T651 Aluminum Alloy, SURFACE
TECHNOLOGY 51, 263 (2022).
14. Ö. Seçgin and M. Z. Sogut, Parametric Optimization of Machining Criteria for Al 6068 Aluminum
Alloy using in Manufacturing Process of Aircraft, Journal of Aeronautics, Astronautics and
Aviation 53, 289 (2021).
15. M. Ay and A. Etyemez, Optimization of Effects of Cutting Parameters and Cutting Tool Path by
using Grey Based Taguchi Method, Acta Phys Pol A 134, 125 (2018).
16. V. H. Nguyen, T. T. Le, and A. T. Nguyen, Optimization of Process Parameter in High-Speed
Milling AA6061 Using SVR and NSGA-II, Lecture Notes in Mechanical Engineering 149 (2024).
17. P. P. Das, Application of EDAS method in parametric optimization of vertical milling operation
on Al 6063, AIP Conf Proc 2786, (2023).
18. W. H. Wang, X. Cheng, Q. L. Sun, F. Wang, and X. M. Yang, Study on tool wear for mircomilling
of 6061 aluminium alloy, IOP Conf Ser Mater Sci Eng 504, 012084 (2019).
19. S. Rajendran and S. C. Rasheedali, Optimization of process parameters for peripheral milling
operation using Taguchi grey relational analysis, AIP Conf Proc 2134, (2019).

20. S. S. Warsi, M. H. Agha, R. Ahmad, S. H. I. Jaffery, and M. Khan, Sustainable turning using multi-
objective optimization: a study of Al 6061 T6 at high cutting speeds, International Journal of

Advanced Manufacturing Technology 100, 843 (2019).
21. S. Tesic, D. Cica, S. Borojevic, B. Sredanovic, M. Zeljkovic, D. Kramar, and F. Pusavec,
Optimization and Prediction of Specific Energy Consumption in Ball-End Milling of Ti-6Al-4V
Alloy Under MQL and Cryogenic Cooling/Lubrication Conditions, International Journal of
Precision Engineering and Manufacturing – Green Technology 9, 1427 (2022).
22. P. HEMA, G. PADMANABHAN, and T. ESWAR, EXPERIMENTAL INVESTIGATION AND
OPTIMIZATION OF MACHINING PARAMETERS IN MILLING OF AL6351 USING
23. P. J. Ross, Taguchi Techniques for Quality Engineering., Singapore.,
https://www.scirp.org/%28S%28vtj3fa45qm1ean45vvffcz55%29%29/reference/ref
erencespapers.aspx?referenceid=1333944.
24. M. T. Anantha, S. Koneru, S. Pyatla, P. P. T. Pillai, T. Buddi, and N. R. Boggarapu, Optimal
Constrained Groove Pressing Process Parameters Applying Modified Taguchi Technique and
Multi-Objective Optimization, Pertanika J Sci Technol 32, 883 (2024).
25. G. Satyanarayana, K. L. Narayana, and B. Nageswara Rao, Identification of Optimum Laser Beam
Welding Process Parameters for E110 Zirconium Alloy Butt Joint Based on Taguchi-CFD
Simulations, Lasers in Manufacturing and Materials Processing 5, 182 (2018).
26. B. V. Dharmendra, S. P. Kodali, and B. Nageswara Rao, A simple and reliable Taguchi approach
for multi-objective optimization to identify optimal process parameters in nano-powder-mixed
electrical discharge machining of INCONEL800 with copper electrode, Heliyon 5, (2019).
27. S. Koneru, A. Srinath, and B. Nageswara Rao, Multiobjective optimization for the optimal heat
pipe working parameters based on Taguchi’s design of experiments, Heat Transfer 51, 2510 (2022).
28. M. T. Anantha, T. Buddi, and N. R. Boggarapu, Multi-objective optimization basing modified
Taguchi method to arrive the optimal die design for CGP of AZ31 magnesium alloy, International
Journal on Interactive Design and Manufacturing 18, 6451 (2023).
29. A. M. Tanuja, H. Mugutkar, S. Pyatla, K. P. K. Reddy, and B. N. Rao, Multi- Objective
Optimization to Specify Optimal Friction Stir Welding Process Parameters for Dissimilar Mg Alloys
(AZ31 and ZM21), International Journal of Vehicle Structures and Systems 16, 50 (2024).
30. M. T. Anantha, S. Koneru, P. P. Thiruvambalam Pillai, N. R. Boggarapu, T. Buddi, K. I. Usanova,
and R. Deorari, Surface quality improvement of AZ31 Mg alloy by a combination of modified
Taguchi method and simple multi objective optimization procedure, Cogent Eng 11, (2024).
31. K. P. Kumar Reddy, S. R. Kumar, and B. Nageswara Rao, Multi-objective optimization for
minimize cutting force and power consumption in corn stalk chopping processes, Heliyon 10,
(2024).
32. K. P. K. Reddy, B. N. Rao, M. N. Nazeemudheen, S. K. Manwatkar, and S. V. S. N. Murty, Selection
of Optimal Process Parameters to Obtain Defect-Free Builds in IN718 Made by Laser Powder Bed
Fusion, J Mater Eng Perform 33, 10228 (2023).
33. R.K. Prasanth Kumar, N. R. Boggarapu, and S. V. S. Narayana Murty, Multi- objective optimization
to specify optimal selective laser melting process parameters for SS316 L powder, Multidiscipline
Modeling in Materials and Structures 20, 59 (2023).