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Optimizing turning operation of St37 steel using grey relational analysis | ||
| Journal of Computational & Applied Research in Mechanical Engineering (JCARME) | ||
| مقاله 6، دوره 3، شماره 2، شهریور 2014، صفحه 135-144 اصل مقاله (809.46 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22061/jcarme.2014.67 | ||
| نویسندگان | ||
| S. Khalilpourazary* ؛ P. M. Kashtiban؛ N. Payam | ||
| Department of Mechanical Engineering, Urmia University of Technology, Urmia, Iran | ||
| تاریخ دریافت: 05 مهر 1391، تاریخ بازنگری: 29 مرداد 1392، تاریخ پذیرش: 06 شهریور 1392 | ||
| چکیده | ||
| Nowadays, in order to reach minimum production cost in machining operations, various optimization methods have been proposed. Since turning operation has different parameters affecting the workpiece quality, it was selected as a complicated manufacturing method in this paper. To reach sufficient quality, all influencing parameters such as cutting speed, federate, depth of cut and tool rake angle were selected as input parameters. Furthermore, both surface roughness and tool life were considered as the objectives. Also, ST37 steel and M1 high speed steel (HSS) were selected as workpiece material and tool, respectively. Subsequently, grey relational analysis was performed to elicit optimal values for the mentioned input data. To achieve this goal, first, degree of freedom was calculated for the system and the same experiments were performed based on the target values and number of considered levels, leading to calculating grey relational generating, grey relational coefficient and grey relational grade. As the next step, the grey relational graph was sketched for each level. Finally, optimum values of the parameters were obtained for better surface roughness and tool life. It was shown that the presented method in the turning operation of ST37 led to high surface quality and tool life. | ||
| کلیدواژه‌ها | ||
| Turning؛ Optimization؛ Grey analysis؛ Sourface roughness؛ Tool life | ||
| مراجع | ||
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[1] F. Klocke, Manufacturing Processes 1: Cutting, First ed., Springer, New York, pp. 110-134, (2011).
[2] B. C. Routara, B. K. Nanda, A. K. Sahoo, D. N. Thatoi and B. B. Nayak, “Optimization of multiple performance characteristics in abrasive jet machining using grey relational analysis”, Int. J. Manufact. Technol. Manag., Vol. 24, No. 2, pp. 4-22, (2011).
[3] E. Sori, R. Narimani and E. Rohanie esfhani, “Optimization turning parameters using micro genetic algorithm”, Proc. of 5th National Manufacturing Conference, Najafabad, Iran, pp. 141-146, (2007).
[4] J. P. Davim, “Design of optimization of cutting parameters for turning metal matrix composites based on the orthogonal arrays”, J. Mater. Process. Technol., Vol. 132, No.1, pp. 340-344, (2003).
[5] C. L. Lin, “Use of the taguchi method and grey relational analysis to optimize turning operations with multiple performance characteristics”, Mater. Manufact. Process., Vol. 19, No. 2, pp. 209-220, (2004).
[6] A. Manna and B. Bhattacharyya, “Investigation for optimal parametric combination for achieving better surface finish during turning of Al/SiC-MMC”, Int. J. Adv. Manufact. Technol., Vol. 23, No. (9-10), pp. 658-665, (2004).
[7] M. Nalbant, H. Gokkaya and G. Sur, “Application of taguchi method in the optimization of cutting parameters for surface roughness in turning”, Mater. Des., Vol. 28, No. 4, pp. 1379-1385, (2007).
[8] H. Goolkarpoor, N. Dehghani Samanni and H. Zarepoor Firouzabadi, “The effect of the surface roughnee, cutting surface and temperature on the tool life in turning operation of St37 steel”, Proc. of1th National Mechanic Conference, Majlesi, Iran, pp. 100-106, (2007).
[9] R. Mahdavinezhad, M. Khajeh Afzali and E. Daziani, “Analysis of tool wear in turning operation of St37 steel”, J. Appl. Mech., Vol. 45, No. 3, pp. 77-85, (2011).
[10] M. Kutz, Handbook of Materials Selection, 2nd ed., John Wiley & Sons, Inc., New York, pp. 50-72, (2002).
[11] M. Boccalini and H. Goldenstein, “Solidification of high speed steels”, Int. Mater. Rev., Vol. 46, No. 2, pp.92-115, (2001).
[12] Taegu Technology Company, Cutting Tools Catalogue, Korea Industry, Seoul, pp. 310-315, (2001).
[13] ASM handbook, Metals Handbook: Surface Engineering, First ed., New York, pp. 230-312, (1994).
[14] E. Isakov, Cutting Data for Turning of Steel, First ed., Industrial Press Inc., New York, pp. 102-150, (2009).
[15] A. Sharma and V. Yadava, “Optimization of cut quality characteristics during Nd: YAG laser straight cutting of Ni-Based superalloy thin sheet using grey relational analysis with entropy measurement”, Mater. Manufact. Process., Vol. 26, No. 12, pp. 1522-1529, (2011).
[16] B. Naveen, A. Kumar, S. Maheshwari and C. Sharma, “Optimization of electrical discharge machining process with Cu-W powder metallurgy electrode using grey relation theory”, Int. J. Mach. Mach. Mater., Vol. 9, No. 2, pp. 103-115, (2011).
[17] U. Caydas and A. Hascalik, “Use of the grey relational analysis to determine optimum laser cutting parameters with multi-performance characteristics”, Optics & Laser Technol., Vol. 40, No. 7, pp. 987-994, (2008).
[18] D. K. Panda, “Modelling and optimization of multiple process attributes of electro discharge machining process by using a new hybrid approach of neuro–grey modeling”, Mater. Manufact. Process, Vol. 25, No. 6, pp. 450-461, (2010).
[19] C. J. Tzeng, Y. H. Lin, Y. K. Yan and M. C. Jeng, “Optimization of turning operations with multipleperformance characteristics using the taguchi methodand grey relational analysis”, J.Mater. Process. Technol., Vol. 209, No. 6, pp. 2753-2759, (2009).
[20] S. Khalilpourazary and P. Nasib, “Optimization of the tool wear, machining rate and overcut of metallic composite Al-4Cu-6Si-10wt%SiCP in EDM drilling operation”, Proc.of 21th Annual International Conference on Mechanical Engineering (ISME2013), Tehran, Iran, pp.10-17, (2013).
[21] K. Palanikumara, B. Lathab, V. S. Senthilkumarc and J. Paulo, “Analysis on drilling of glass fiber–reinforced polymer (GFRP) composites using grey relational analysis”, Mater. Manufact. Process., Vol. 27, No. 3, pp. 297-305, (2012).
[22] J. A. Barriosa, A. Cavazosa, L. Leducb and J. Ramírezb, “Fuzzy and fuzzy grey-box modelling for entry temperature prediction in a hot strip mill”, Mater. Manufact. Process., Vol. 26, No.1, pp. 66-77, (2011).
[23] S. Khalilpourazary, P. Nasib and M. Mohammady, “Optimization of the surface roughness and machining rate of metallic composite Al/Sic in EDM machining using grey relational method”, Proc. Of 1th National Manufacturing Conference, Malayer, Iran, pp. 80-86, (2013).
[24] J. Kopac and P. Krajnik, “Robust design of flank milling parameters based on grey-taguchi method”, J. Mater. Process. Technol., Vol. 191, No. (1-3), pp. 400-403, (2007).
[25] S. Datta, A. Bandyopadhyay and P. K. Pal, “Grey-based taguchi method for optimization of bead geometry in submerged arc bead-on-plate welding”, Int. J. Adv. Manufact. Technol., Vol. 39, No. (11-12), pp. 1136-1143, (2008).
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