Selection of Machining Parameters of Face Milling operation for Aluminium with HSS cutter using Response Surface Methodology and Genetic Algorithm
DOI:
https://doi.org/10.24297/jac.v12i16.3001Keywords:
Face milling parameters, Response Surface Methodolog, Material Removal Rate, Surface Roughness, Genetic Algorithm.Abstract
Components used in chemical equipments are produced from forging, extrusion and casting processes with classic dimension tolerances due to its producing ability. So machining processes were introduced for close tolerance assembly and improve the product working efficiencies. At present, lot of machining processes are available for producing chemical equipments such as turning, milling, drilling and grinding etc.,. Milling operation is playing critical role on making the chemical equipment’s components with high accuracy and higher productivity. Face milling operation is one of the milling processes which is used for achieving higher flatness and surface finish of chemical equipment’s parts. Thiswork concentrates the parameters influence on Material Removal Rate (MRR) and Surface Roughness (SR) by using aluminium as work piece material. Actually, aluminium alloy has the most significant in chemical industries because of its inherent properties such as, corrosive resistance , low weight to strength ratio. The milling parameters such as feed rate, spindle speed  and depth of cut are selected as parameters for improving the quality and productivity. This work put together the link between input and response variables for developing the face milling performances. The Response Surface Methodology (RSM) is employ for making the link between dependent and independent variables. Building the empirical model by conducting regression analysis The performance of developed regression models are verified with experimental results. Verification results show the developed models have best agreement with experimental results. The developed models are used for achieving the best input parameters by using Genetic Algorithm (GA). Finally, the optimal parameters are evaluated by GA.
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References
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26. Kannan S, Baskar N, Varatharajulu M and Suresh kumar B,2015, ‘Modeling and optimization of face milling parameters on brass component using response surface methodology and genetic algorithm’, International Journal of Applied Engineering Research, 2015, 10 (76), pp. 219 – 224
27. Kannan S, Baskar N, Suresh kumar B and Varatharajulu M , 2016,‘ Optimization of face milling parameters for material removal rate and surface roughness on inconel 718 using response surface methodology and genetic algorithm ’, Asian Journal of Research in Social Sciences and Humanities , 6,( 9),pp. 1198-1211.
28. Suresh kumar B, Vijayan V and Baskar N, 2016, “Optimization of drilling process parameters for material removal rate and surface roughness on titanium alloy using response surface methodology and fire fly algorithmâ€, Asian Journal of Research in Social Sciences and Humanities, 65, 1251-1269.
29. Venkata Rao R and Pawar PJ, 2010,Parameter optimization of a multi-pass milling process using non-traditional optimization algorithmsâ€, Journal of Applied Soft Computing, 10, pp. 445 – 456
30. Alisina Toloei, Vesselin Stoilov and Derek Northwood ,2013, ‘The Relationship Between Surface Roughness and Corrosion, ASME proceedings, Advanced Manufacturing.
31. Sukumar MS , Venkata Ramaiah P and Nagarjun A,2014 “Optimization and prediction of parameters in face milling of al-6061 using taguchi and ann approachâ€, Procedia Engineering ,17, pp.365 – 371.
32. Varatharajulu M, Loganathan C & Baskar N, “Influence of cutting parameters on burr height and burr thickness in drilling of Duplex 2205 using Solid Carbideâ€, International Journal of ChemTech Research, Vol. 8, No. 2, 2015, pp. 768 – 777.
33. Varatharajulu M, Loganathan C & Baskar N, “Influence of cutting parameters on roughness and roundness in drilling of Duplex 2205 using High Speed Steelâ€, International Journal of Applied Engineering Research, Vol.10, No. 76, 2015, pp. 129 – 136.
34. Varatharajulu M, Loganathan C, Baskar N & Kannan S, “Influence of cutting parameters on burr height and burr thickness in drilling of Duplex 2205 using High Speed Steelâ€, International Journal of Applied Engineering Research Vol. 10, No. 76, 2015, pp. 381 – 388.
2. Nafis Ahmad 2005, ‘Optimization of cutting parameters for end milling operation by soap based genetic algorithm’, International Conference On Mechanical Engineering (ICME2005), pp.1-5.
3. Neerajkumar 2014, ‘An overview of optimization techniques for CNC milling machine’, International Journal of Engineering, Management, Science, vol.1, no.5. pp.13-16
4. Vikas pare 2011, ‘Optimization of cutting conditions in end milling process with the approach of particle swarm optimization’, International Journal of Mechanical and Industrial Engineering, vol.1, no.2, pp.21-25.
5. Prajina, NV 2013 ‘Multi response optimization of CNC end milling using response surface methodology and desirability function’, International Journal Applied Engineering Research, vol. 6,no.6,
pp.739-746.
6. Lohithaksha M Maiyar, Ramanujam, R, Venkatesan, K and Jeraldd, J 2013, ‘ Optimization of machining parameters for end milling of inconel 718 super alloy using taguchi based grey relational analysis’, Procedia Engineering, vol.64, no.3, pp. 1276 – 1282
7. Balinder sing, Rajesh Khanna, Kapilkoyal and Pawan Kumar 2014, ‘Optimization of input process parameters in cnc milling machine of en24 steel’, International Journal of Research in Mechanical Engineering & Technology, vol.4, no. 1, pp.40-47
8. Naggendraparashar,BS & Mittal, RK 2003, ‘Elements of manufacturing processes’, Prentice Hall of India (P) Ltd.
9. Kalpak Jain, S 1995, ‘Manufacturing engineering and technology’, Addison-Wesley Publishing Company
10. Toloueirad, M &Bidhendi, IM 1997 “On the optimization of machining parameters for milling operationâ€, International Journal of Machine Tools & Manufacture, vol.37, no.1, pp.1-16.
11. Montgomery, DC 1990, ‘Introduction to statistical quality control’ 2nd edition, Wiley. New York
12. Indrajit Mukherjee &Pradip Kumar Ray 2006, ‘A review of optimization techniques in metal cutting processes’, Computers & Industrial Engineering , vol.50, no.1, pp. 15–34
13. Durga Prasad, KG, Prasad, MV &VenkataSubbaiah, K 2015, ‘Optimization of process parameters in CNC end milling of glass - fibre reinforced plastic’ International Journal for Research in Emerging Science and Technology, vol.2, no.6, pp. 60-67.
14. Ali R Yildiz 2013, ‘A new hybrid differential evolution algorithm for the selection of optimal machining parameters in milling operations’, Applied Soft Computing, vol. 13, pp.1561–1566
15. Barathiraja S and Baskar N 2012, “Application of particle swarm optimization technique for achieving desired milled surface roughness in minimum machining timeâ€, International Journal of Expert Systems with Applications, 39, 5982 - 5989.
16. Liang Gao, Jida Huang and Xinyu Li, 2012, ‘An effective cellular particle swarm optimization for parameters optimization of a multi-pass milling process’, Applied Soft Computing, vol.12, no.11,pp. 3490–3499.
17. Baskar N, Asokan P and Prabaharan G, 2005,"Optimization of machining parameters for milling operations using non-conventional methods." The International Journal of Advanced Manufacturing Technology,25, 1078 - 1088.
18. Suresh Kumar. B and Baskar. N 2012“Integration of fuzzy logic with response surface methodology for thrust force and surface roughness modeling of drilling on titanium alloyâ€, International journal of advanced manufacturing technology, 65, pp.1501 – 1514
19. Francicus and Uroszuperl, 2006 ‘Approach to optimization of cutting conditions by using artificial neural networks’, Journal of Material Processing Technology,173, pp.281 – 290
20. Wang J . 1993, ‘ Multiple objective optimization of machining operations based on neural networks’, International Journal of Advanced Manufacturing Technology, 8, pp. 235 – 243
21. Domnita Fratila and Cristian Caizar, 2011,Application of taguchi method to selection of optimal lubrication and cutting conditions in face milling of almg3â€, Journal of Cleaner Production, 2011, 19, pp. 640 – 645.
22. Senthilkumaar JS, Selvarani P and Arunachalam RM, 2015, ‘Selection of machining parameters based on the analysis of surface roughness and flank wear in finish turning and facing of inconel 718 using taguchi technique’ , Emirates Journal for Engineering, 15 (2), pp. 7-14.
23. Gianni Campatelli, Lorenzo Lorenzini and Antonio Scippa,2014, “optimization of process parameters using a response surface method for minimizing power consumption in the milling of carbon steelâ€, Journal of Cleaner Production, 66, pp.309 – 316.
24. Kannan S and Baskar N 2013, “modeling and optimization of face milling operation based on response surface methodology and genetic algorithmâ€, International Journal of Engineering and Technology, 5,pp.4164 – 4176.
25. Kannan S, Baskar N, Suresh kumar B and Varatharajulu M , 2015,‘Investigation on optimum cutting condition in face milling of copper with HSS cutter using response surface methodology and genetic algorithm’, International Journal of Applied Engineering Research,10 (57), pp.243 - 247.
26. Kannan S, Baskar N, Varatharajulu M and Suresh kumar B,2015, ‘Modeling and optimization of face milling parameters on brass component using response surface methodology and genetic algorithm’, International Journal of Applied Engineering Research, 2015, 10 (76), pp. 219 – 224
27. Kannan S, Baskar N, Suresh kumar B and Varatharajulu M , 2016,‘ Optimization of face milling parameters for material removal rate and surface roughness on inconel 718 using response surface methodology and genetic algorithm ’, Asian Journal of Research in Social Sciences and Humanities , 6,( 9),pp. 1198-1211.
28. Suresh kumar B, Vijayan V and Baskar N, 2016, “Optimization of drilling process parameters for material removal rate and surface roughness on titanium alloy using response surface methodology and fire fly algorithmâ€, Asian Journal of Research in Social Sciences and Humanities, 65, 1251-1269.
29. Venkata Rao R and Pawar PJ, 2010,Parameter optimization of a multi-pass milling process using non-traditional optimization algorithmsâ€, Journal of Applied Soft Computing, 10, pp. 445 – 456
30. Alisina Toloei, Vesselin Stoilov and Derek Northwood ,2013, ‘The Relationship Between Surface Roughness and Corrosion, ASME proceedings, Advanced Manufacturing.
31. Sukumar MS , Venkata Ramaiah P and Nagarjun A,2014 “Optimization and prediction of parameters in face milling of al-6061 using taguchi and ann approachâ€, Procedia Engineering ,17, pp.365 – 371.
32. Varatharajulu M, Loganathan C & Baskar N, “Influence of cutting parameters on burr height and burr thickness in drilling of Duplex 2205 using Solid Carbideâ€, International Journal of ChemTech Research, Vol. 8, No. 2, 2015, pp. 768 – 777.
33. Varatharajulu M, Loganathan C & Baskar N, “Influence of cutting parameters on roughness and roundness in drilling of Duplex 2205 using High Speed Steelâ€, International Journal of Applied Engineering Research, Vol.10, No. 76, 2015, pp. 129 – 136.
34. Varatharajulu M, Loganathan C, Baskar N & Kannan S, “Influence of cutting parameters on burr height and burr thickness in drilling of Duplex 2205 using High Speed Steelâ€, International Journal of Applied Engineering Research Vol. 10, No. 76, 2015, pp. 381 – 388.
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Published
2016-11-11
How to Cite
S, K., B, S. K., N, B., & M, V. (2016). Selection of Machining Parameters of Face Milling operation for Aluminium with HSS cutter using Response Surface Methodology and Genetic Algorithm. JOURNAL OF ADVANCES IN CHEMISTRY, 12(16), 4938–4949. https://doi.org/10.24297/jac.v12i16.3001
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