Prediction of cutting force in turning of UD-GFRP using mathematical model and simulated annealing

doi:10.1007/s11465-012-0343-2

Front Mech Eng

0, Vol.

Issue () : 417-426 https://doi.org/10.1007/s11465-012-0343-2

RESEARCH ARTICLE

Prediction of cutting force in turning of UD-GFRP using mathematical model and simulated annealing

Meenu GUPTA, Surinder Kumar GILL(

)

Department of Mechanical Engineering, National Institute of Technology, Kurukshetra 136119, India

Download: PDF(174 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

Glass fiber reinforced plastics (GFRPs) composite is considered to be an alternative to heavy exortic materials. According to the need for accurate machining of composites has increased enormously. During machining, the obtaining cutting force is an important aspect. The present investigation deals with the study and development of a cutting force prediction model for the machining of unidirectional glass fiber reinforced plastics (UD-GFRP) composite using regression modeling and optimization by simulated annealing. The process parameters considered include cutting speed, feed rate and depth of cut. The predicted values radial cutting force model is compared with the experimental values. The results of prediction are quite close with the experimental values. The influences of different parameters in machining of UD-GFRP composite have been analyzed.

Keywords UD-GFRP ANOVA radial cutting force PCD tool Taguchi method regression analysis simulated annealing multi objective techniques

Corresponding Author(s): GILL Surinder Kumar,Email:surinder.asd@gmail.com

Issue Date: 05 December 2012

Cite this article:

Meenu GUPTA,Surinder Kumar GILL. Prediction of cutting force in turning of UD-GFRP using mathematical model and simulated annealing[J]. Front Mech Eng, 0, (): 417-426.

URL:

https://academic.hep.com.cn/fme/EN/10.1007/s11465-012-0343-2
https://academic.hep.com.cn/fme/EN/Y0/V/I/417

1	Strategic Engineering (P) Ltd. Chennai, Piping Manual , 2002.
2	Ramkumar J, Aravindan S, Malhotra S K, Krishnamurthy R. An enhancement of the machining performance of GFRP by oscillatory assisted drilling. International Journal of Advanced Manufacturing Technology , 2004, 23(3-4): 240–244 doi: 10.1007/s00170-003-1660-8
3	Caprino G, Nele L.Cutting forces in orthogonal cutting of unidirectional GFRP composites. Journal of Engineering Materials and Technology , 1996, 118(3), 419–425
4	Koplev A, Lystrup A, Vorm T. The cutting process, chips and cutting forces in machining CFRP. Composites , 1983, 14(4), 371–376
5	Yang W H, Tarng Y S. Design optimization of cutting parameters for turning operations based on the Taguchi method. Journal of Materials Processing Technology , 1998, 84(1-3): 122–129 doi: 10.1016/S0924-0136(98)00079-X
6	Zuperl U, Cus F, Mursec B, Ploj T. A hybrid analytical-neural network approach to the determination of optimal cutting conditions. Journal of Materials Processing Technology , 2004, 157-158 (20): 82–90 doi: 10.1016/j.jmatprotec.2004.09.019
7	Wang X M, Zhang L C. Machining damage in unidirectional fibre-reinforced plastics. In: Proceedings of the Third International Conference on Abrasive Technology, Brisbane, Australia , 1999
8	Wang X M, Zhang L C. An experimental investigation into the orthogonal cutting of unidirectional fibre-reinforced plastics. International Journal of Machine Tools & Manufacture , 2003, 43(10): 1015–1022 doi: 10.1016/S0890-6955(03)00090-7
9	Mahdi M, Zhang L C. A finite element model for the orthogonal cutting of fibre-reinforced composite materials. Journal of Materials Processing Technology , 2001, 113(1-3): 373–377 doi: 10.1016/S0924-0136(01)00675-6
10	Mahdi M, Zhang L C. An adaptive three-dimensional finite element algorithm for the orthogonal cutting of composite materials. Journal of Materials Processing Technology , 2001, 113(1-3): 368–372 doi: 10.1016/S0924-0136(01)00676-8
11	Sun F H, Wu Z Y, Zhong J W, Chen M. High speed milling of SiC particle reinforced aluminum-based MMC with coated carbide inserts. Key Engineering Materials , 2004, 274-276: 457–462 doi: 10.4028/www.scientific.net/KEM.274-276.457
12	Davim J P, Mata F. Influence of cutting parameters on surface roughness in turning glass-fiber-reinforced-plastics using statistical analysis. Industrial Lubrication and Tribology , 2004, 56(5): 270–274
13	Davim J P, Mata F. Optimisation of surface roughness on turning fiber reinforced plastics (FRPs) with diamond cutting tools. International Journal of Advanced Manufacturing Technology , 2005, 26(4): 319–323 doi: 10.1007/s00170-003-2006-2
14	Sreejith P S, Krishnamurthy R, Malhotra S K, Narayanasamy K. Evaluation of PCD tool performance during machining of carbon/phenolic ablative composites. Journal of Materials Processing Technology , 2000, 104(1-2): 53–58 doi: 10.1016/S0924-0136(00)00549-5
15	Isik B, Kentli A. Multicriteria optimization of cutting parameters in turning of UD-GFRP materials considering sensitivity. International Journal of Advanced Manufacturing Technology , 2009, 44(11,12): 1144–1153 doi: 10.1007/s00170-009-1927-9
16	Hussain S A, Pandurangadu V, kumar K P. Machinability of glass fiber reinforced plastic (GFRP) composite materials. International Journal of Engineering, Science and Technology , 2011, 3 (4): 103–118
17	Batalha M O. Introduction to Production Engineering. Rio de Janeiro: Elsevier Publisher , 2008
18	Chaves A A, Biajoli F L, Mine O M, Souza M J F. Exact and heuristic modeling for solving a generalization of the travelling salesman problem. In: Brazilian Symposium of Operational Research, Sobrapo , 2004, 1364–1378
19	Duran O, Barrientos R, Cosalter L A. Application of genetic algorithm and Taylor expanded equation in obtaining maximum efficiency range. In: Proceedings of IV Brazilian Congress on Manufacturing Engineering, Cobef , 2007
20	Dhavamani C, Alwarsamy T. Optimization of cutting parameters of composite materials using genetic algorithm. European Journal of Scientific Research , 2011, 63(2): 279–285
21	Palanikumar K, Latha B, Senthilkumar V S, Karthikeyan R. Multiple performance optimizations in machining of GFRP composites by a PCD tool using non-dominated sorting genetic algorithm (NSGA-II). Metals and Materials International , 2009, 15(2): 249–258 doi: 10.1007/s12540-009-0249-7
22	Rajasekaran T, Palanikumar K, Vinayagam B K. Application of fuzzy logic for modeling surface roughness in turning CFRP composites using CBN tool. Production Engineering , 2011, 5(2): 191–199
23	Jain R K, Jain V K. Optimum selection of machining conditions in abrasive flow using neural networks. Journal of Materials Processing Technology , 2000, 108(1): 62–67 doi: 10.1016/S0924-0136(00)00621-X
24	Ingber L. Simulated annealing: Practice versus theory. Mathematical and Computer Modelling , 1993, 18(11): 29–57 doi: 10.1016/0895-7177(93)90204-C
25	Goffe W L, Ferrier G D, Rogers J. Global optimization of statistical functions with simulated annealing. Journal of Econometrics , 1993, 60: 65–99 .
26	Saravanan R, Asokan P, Sachithanandam M. Comparative analysis of conventional and non-conventional optimizations techniques for CNC turning process. International Journal of Advanced Manufacturing Technology , 2001, 17(7): 471–476 doi: 10.1007/s001700170146
27	Sarker R, Yao X. Simulated annealing and joint manufacturing batch-sizing. Yugoslav Journal of Operations Research , 2003, 13(2): 245–259 doi: 10.2298/YJOR0302245S
28	Kolahan F, Abachizadeh M. Optimizing turning parameters for cylindrical parts using simulated annealing method. World Academy of Science, Engineering and Technology , 2008, 46: 436–439
29	Yang S, Srinivas J, Mohan S, Lee D, Balaji S. Optimization of electric discharge machining using simulated annealing. Journal of Materials Processing Technology , 2009, 209(9): 4471–4475 doi: 10.1016/j.jmatprotec.2008.10.053
30	Coppini N L, Librantz A F H, Rosa A F C, Carvalho A A M. Simulated annealing applied to minimize the idleness and maximize the contribution margin for generics flexibles machining cells. In: Proceedings of 2nd International Conference on Engineering Optimization, Lisbon, Portugal , 2010
31	Farhad K A, Hamid K, A statistical approach for predicting and optimizing depth of cut in AWJ machining for 6063-T6 Al alloy. International Journal of Aerospace and Mechanical Engineering , 2011, 2(5): 143–146
32	Harvey K, Ansell M P. Improved timber connections using bonded-in GFRP rods. http://timber.ce.wsu.edu/Resources/papers/p4.pdf
33	Ross P J. Taguchi Techniques for Quality Engineering. New York: McGraw-Hills Book Company, 1988
34	Kirkpatrick S, Gelatt C D Jr, Vecchi M P. Optimization by simulated annealing. Science , 1983, 220: 671–680 doi: 10.1126/science.220.4598.671 pmid:17813860
35	Metropolis N, Rosenbluth A, Telland Teller E. Equation of state calculations by fast computing machines. Journal of Chemical Physics , 1953, 21(6): 1087 doi: 10.1063/1.1699114
36	Balram S. Study of simulated annealing based algorithms for multiobjective optimization of a constrained problem. Computers & Chemical Engineering , 2004, 28(9): 1849–1871 doi: 10.1016/j.compchemeng.2004.02.037
37	Eglese R W. A tool for operational research. European Journal of Operational Research , 1990, 46(3): 271–281 doi: 10.1016/0377-2217(90)90001-R
38	Venkataraman P. Applied Optimization with MATLAB Programming, New York, Wiely , 2002, 360-385

[1]	Zilin HUANG,Gang WANG,Shaopeng WEI,Changhong LI,Yiming RONG. Process improvement in laser hot wire cladding for martensitic stainless steel based on the Taguchi method[J]. Front. Mech. Eng., 2016, 11(3): 242-249.
[2]	Surinder Kumar GILL, Meenu GUPTA, P. S. SATSANGI. Prediction of cutting forces in machining of unidirectional glass fiber reinforced plastics composite[J]. Front Mech Eng, 2013, 8(2): 187-200.
[3]	Rupesh CHALISGAONKAR, Jatinder KUMAR. Optimization of WEDM process of pure titanium with multiple performance characteristics using Taguchi’s DOE approach and utility concept[J]. Front Mech Eng, 2013, 8(2): 201-214.
[4]	Kamal JANGRA, Sandeep GROVER, Aman AGGARWAL. Optimization of multi machining characteristics in WEDM of WC-5.3%Co composite using integrated approach of Taguchi, GRA and entropy method[J]. Front Mech Eng, 2012, 7(3): 288-299.
[5]	Rajesh SIRIYALA, Gopala Krishna ALLURU, Rama Murthy Raju PENMETSA, Muthukannan DURAISELVAM. Application of grey-taguchi method for optimization of dry sliding wear properties of aluminum MMCs[J]. Front Mech Eng, 2012, 7(3): 279-287.
[6]	Christopher John NASSAU, N. Scott LITOFSKY, Yuyi LIN. Analysis of spinal lumbar interbody fusion cage subsidence using Taguchi method, finite element analysis, and artificial neural network[J]. Front Mech Eng, 2012, 7(3): 247-255.
[7]	ZHANG Pengxian, ZHANG Hongjie, CHEN Jianhong, MA Yuezhou. Quality monitoring of resistance spot welding based on electrode displacement characteristics analysis[J]. Front. Mech. Eng., 2007, 2(3): 330-335.

Viewed

Full text

Abstract

Cited

Shared

Discussed