Optimization of Turning Operations by Using a Hybrid Genetic Algorithm with Sequential Quadratic Programming

 

A. Belloufi*^1,3, M. Assas², I. Rezgui³

 

¹ Department of Mechanical Engineering, Université Mohamed Khider, 07000 Biskra, Biskra, Algeria, *abelloufi@yahoo.fr.

² Laboratoire de Recherche en Productique (LRP), Department of Mechanical Engineering, University Hadj Lakhder, Batna Batna, Algeria.

³ Université Kasdi Merbah Ouargla, Route de Ghardaia 30000, Ouargla Ouargla, Algeria.

 

ABSTRACT

The determination of optimal cutting parameters is one of the most important elements in any process planning of metal parts. In this paper, a new hybrid genetic algorithm by using sequential quadratic programming is used for the optimization of cutting conditions. It is used for the resolution of a multipass turning optimization case by minimizing the production cost under a set of machining constraints. The genetic algorithm (GA) is the main optimizer of this algorithm whereas SQP Is used to fine tune the results obtained from the GA. Furthermore, the convergence characteristics and robustness of the proposed method have been explored through comparisons with results reported in literature. The obtained results indicate that the proposed hybrid genetic algorithm by using a sequential quadratic programming is effective compared to other techniques carried out by different researchers.

Keywords: multipass turning, genetic algorithm, sequential quadratic programming, optimization of cutting conditions.

 

DESCARGAR ARTÍCULO EN FORMATO PDF

 

References

[1] R. Q. Sarinas et al, "Genetic algorithm-based multi-objective optimization of cutting parameters in turning processes", Eng Appl Artif Intel, 19, 127-133, 2006.         [ Links ]

[2] Y. C. Wang, "A note on optimization of multi-pass turning operations using ant colony system", Int J Mach Tool Manu, 47 (12-13):2057-2059, 2007.         [ Links ]

[3] S. XIE and Y. Guo, "Intelligent selection of machining parameters in multi-pass turnings using a GA-based approach", J Comput Inform Syst, 7:5, 1714-1721, 2011.         [ Links ]

[4] S. E. Kilic et al, "A computer-aided graphical technique for the optimization of machining conditions", Computers Ind. 22, 319-326, 1993.         [ Links ]

[5] D. S. Ermer and D.C. Patel, "Maximization of production rate with constraints by linear programming and sensitivity analysis", Proc. Second North American Metalworking Research Conference WI, 1974.         [ Links ]

[6] J. S. Agapiou, "The optimization of machining operations based on a combined criterion, Part 2: Multipass operations", Computers Ind. Trans, ASME 114, 508-513, 1992.         [ Links ]

[7] Y. C. Shin and Y.S. Joo, "Optimization of machining conditions with practical constraints", Int. J. Prod Res, 30(12), 2907-2919, 1992.         [ Links ]

[8] D. S. Ermer, "Optimization of the constrained machining economics problem by geometric programming", Comput Ind, ASME 93, 1067-1072, 1971.         [ Links ]

[9] P. G. Petropoulos, "Optimal selection of machining rate variable by geometric programming", Int. J. Prod Res. 11(4), 305-314, 1973.         [ Links ]

[10] M. C. Chen and D. M. Tsai, "A simulated annealing approach for optimization of multi-pass turning operations", Int. J. Prod Res, 34 (10), 2803-2825, 1996.         [ Links ]

[11] M. C. Chen and K. Y. Chen, "Optimization of multipass turning operations with genetic algorithms: a note", Int. J. of Pro Res, 41 (14), 3385-3388, 2003.         [ Links ]

[12] J. Srinivas et al, "Optimization of multi-pass turning using particle swarm intelligence", Int. J. Adv Manu Tech, 40 (1-2):56-66, 2009.         [ Links ]

[13] R. S. Sankar et al, "Selection of machining parameters for constrained machining problem using evolutionary computation", Int. J. Adv Manu Tech, 32 (910), 892-901, 2007.         [ Links ]

[14] M. C. Chen, "Optimizing machining economics models of turning operations using the scatter search approach", Int. J. of Prod Res, 42 (13): 2611-2625, 2004.         [ Links ]

[15] R. H. Philipson and A. Ravindran, "Application of mathematical programming to metal cutting". Math Program Study 11, 116-134. 1979.         [ Links ]

[16] R. V. Narang and G. W. Fischer, "Development of a frame work to automate process planning functions and to determine machining parameters". Int. J. of Prod Res, 31, 1921-1942. 1993.         [ Links ]

[17] K. Vijayakumar et al, "Optimization of multi-pass turning operations using ant colony system", Int J Mach Tool Manu, 43 (15), 1633-1639, 2003.         [ Links ]

[18] S. S. Rao, "Engineering optimization theory and practice", fourth edition, ISBN 978-0-470-18326-6 (cloth), 2009.         [ Links ]

[19] S. Hiwa et al, "Hybrid optimization using direct, GA, and SQP for global exploration". IEEE Congress on Evolutionary Computation, Sept. 2007, pages 1709-1716.         [ Links ]

[20] F. Yaman and A. E. Yilmaz, "Impacts of Genetic Algorithm Parameters on the Solution Performance for the Uniform Circular Antenna Array Pattern Synthesis Problem", J. Appl Res Technol, Vol 8, pp. 378-394, 2010        [ Links ]