Particle Swarm Optimisation of Hole Quality Characteristics in Laser Trepan Drilling of Inconel 718
Abstract
Inconel-718 is a nickel based super alloy and is extensively in use for working at very high temperature (upto 2000 °C) such as aero engine gas path equipment, nuclear equipment etc. Drilling micro size hole in such material with laser beam has been a proven choice and laser drilling process produces geometrically and dimensionally improved hole. Hole geometrical features can be improved further if laser drilling system operated at optimal input parameter setting. This paper experimentally investigates the behavior of hole geometrical features hole circularity and hole taper in laser trepan drilling of Inconel -718 sheet. Optimal value of laser input parameters for improved hole circularity and reduced hole taper have been suggested with the help of computational intelligence technique particle swarm optimisation. The effect of each laser input parameter on hole quality characteristics are also discussed and demonstrated graphically. Finally the experimental validation of the predicted results has been carried out.
References
V. K. Jain, Advanced Machining Processes, Allied publisher pvt. New Delhi, 2005.
E.O.Ezugwu, Z.M. Wang andA.R. Machado, The machinability of nickel based alloys-a review. Journal of Materials Processing Technology , 86(1999) 1–16.
C.Y. Yeo , S.C. Tam , S .Jana and M.W.S. Lau, A technical review of the laser drilling of aerospace materials, Journal of Materials Processing Technology; 42(1994)15–49.
G. Chyryssouris, Laser Machining , Springer. New york, 2005.
A. K. Dubey and V. Yadava, Laser beam machining – A review, International Journal of Machine Tools & Manufacture, 48 (2008) 609-628.
S. Kumar, A.K. Dubey and A.K. Pandey, Computer-Aided Genetic Algorithm Based Multi-Opbjective Optimization of Laser Trapan Drilling, Internation Journal of Pricision Engineering and Manufacuring , 14 (2013)1119-1125.
I. A. Choudhury, W. C. Chong and G.Vahid, Hole qualities in laser trepanning of polymeric materials, Optics And Lasers in Engineering,50 (2012) 1297–1305.
A.K. Pandey and A.K. Dubey, Taguchi based fuzzy logic optimization of multiple quality characteristics in laser cutting of Duralumin sheet, Optics and Lasers in Engineering, 50 (2012) 328–335
G. Norkey , A.K. Dubey and S. agarwal, Artficla intellegenec based modeling and optimization of heat affcted zone in Nd:YAG laser cutting of duralumin sheet, , Journal of Intelligent & Fuzzy Systems, 27(3)(2014) 1545-1555.
W.T. Chien and S.C. Hou , Investigating the recast layer formed during the laser trepan drilling of Inconel 718 using the Taguchi method, International Journal of Advanced Manufacturing Technology, 33( 2007) 308–316.
R. Goyal and A.K. Dubey, Modeling and optimization of geometrical characteristics in laser trepan drilling of titanium alloy, Journal of Mechanical Science and Technology , 30 (3) (2016) 1281~1293.
S. Marimuthu, M. Antar, J. Dunleavey, D. Chantzis, W. Darlington and P. Hayward, An experimental study on quasi-CW fibre laser drilling of nickel superalloy, Optics and Laser Technology, 94 (2017) 119–127.
K.F.Tamrin, Y.Nukman, I.A.Choudhury and S.Shirley, Multiple-objective optimization in precision laser cutting of different thermoplastics’, Optics andLasersinEngineering, 67(2015)57–65
D. B. Hajdarevic and I. Bijelonja, Experimental and Numerical Investigation of Temperature Distribution and Hole Geometry during Laser Drilling Process, Procedia Engineering, 100 ( 2015 ) 384 – 393.
P. Rajesh, U. Nagaraju , G. Harinath Gowd and T.Vishnu Vardhan, Experimental and parametric studies of Nd:YAG laser drilling on austenitic stainless steel, Internation journal of advanced manufacturing technology, DOI 10.1007/s00170 (2015)7639-4
A.K. Chaudhary A.K. Pandey and A.K. Dubey., Computer Aided Taguchi-FuzzyMulti-Optimization of laser cutting process, Journal of Intelligent & Fuzzy Systems, 26(2)(2014) 801-810.
K.L. Dhaker , A. K. Pandey and B. N. Upadhayay, Experimental Investigation of Hole Diameter in Laser Trepan Drilling of Inconel718 Sheet, Materials Today: Proceedings 4 (2017) 7599–7608.
D.C. Montgomery, Design and analysis of experiments, wiley India, New Delhi, 2009
M. S. Phadke, Quality engineering using robust design, Prentice-hall,NJ, 1989.
B.E.Gillett, Introduction to operation research –A Computer –oriented Algorithmic Approach, Tata McGraw-Hill, New Delhi, 2008
A. K. Pandey and A. K Dubey, Simultaneous optimization of multiple quality characteristics in laser cutting of titanium alloy sheet, Optics & Laser Technology, 44 (2012)1858–1865.
M. Ghoreishi, D.K.Y. Low and L. Li, Compartive statistical analysis of hole taper and circularity in laser percussion drilling , Internation journal of machine tool & Manufacuring , 42 (2002)985-995.
J.Kenned and R.C.Eberhart,. Particle swarm optimization. Proc. IEEE Int'l. Conf. on Neural Networks, IV, 1942–1948. Piscataway, NJ: IEEE Service Center, 2005.
C. P. Mohanty, S. S. Mahapatra and M. R. Singh, A particle swarm approach for multi-objective optimization of electrical discharge machining process, Journal of Intelligence Manufacturing, 27(2016) 1171–1190.
N.Yusup , A.M. Zain and S. Z. Mohd Hashim, Overview of PSO for Optimizing Process Parameters of Machining, Procedia Engineering, 29 (2012) 914 – 923
R.V. Rao, Advanced modeling and optimisation of manufacuring process, 1st ed. Springer, London, 2011.
H.Garg and S.P.Sharma, Multi-objective reliability-redundancy allocation problem using particle swarm optimization, Computers & Industrial Engineering, 64 (2013) 247–255.
S. Garg, K. Patra and S. K. Pal, Particle swarm optimization of a neural network model in a machining process, Indian Academy of Sciences, 39 (3)(2014)533–548.
S.Das , A.Abraham, and A.Konar, Particle Swarm Optimization and Differential Evolution Algorithms: Technical Analysis, Applications and Hybridization Perspectives, Studies in Computational Intelligence, 116(2008) 1–38.
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