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Application of fuzzy logic for modeling surface roughness in turning CFRP composites using CBN tool

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Abstract

In recent days, carbon fiber reinforced polymer (CFRP) composites play a vital role in various engineering and technological applications. They are replacing conventional materials due to their excellent properties. Tubes made of these materials are made up of either hand layup process or filament winding processes and are widely used in aircraft, automobile, sports industries, etc., The objective of this study is to examine the influence of machining parameters combination so as to obtain a good surface finish in turning of CFRP composite by cubic boron nitride (CBN) cutting tool and to predict the surface roughness values using fuzzy modeling. The results indicate that the fuzzy logic modeling technique can be effectively used for the prediction of surface roughness in machining of CFRP composites.

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References

  1. Ying W, Hahn TH (2007) AFM characterization of the interfacial properties of carbon fiber reinforced polymer composites subjected to hygrothermal treatments. Compos Sci Technol 67:92–101

    Google Scholar 

  2. Shanmugam DK, Chen FL, Siores E, Brandt M (2002) Comparative study of jetting machining technologies over laser machining technology for cutting composite materials. Compos Struct 57:289–296

    Article  Google Scholar 

  3. Gaitonde VN, Karnik SR, Campos Rubio J, Esteves Correia A, Abrão AM, Paulo Davim J (2008) Analysis of parametric influence on delamination in high-speed drilling of carbon fiber reinforced plastic composites. J Mater Process Technol 203:431–438

    Article  Google Scholar 

  4. Grzesik W, Brol S (2003) Hybrid approach to surface roughness evaluation in multi stage machining processes. J Mater Process Technol 134:265–272

    Article  Google Scholar 

  5. Palanikumar K (2007) Modeling and analysis for surface roughness in machining glass fibre reinforced plastics using response surface methodology. Mater Des 28:2611–2618

    Article  Google Scholar 

  6. Mohan NS, Ramachandra A, Kulkarni SM (2005) Influence of process parameters on cutting force and torque during drilling of glass–fiber polyester reinforced composites. Compos Struct 71:407–413

    Article  Google Scholar 

  7. Hu NS, Zhang LC (2004) Some observations in grinding unidirectional carbon fibre-reinforced plastics. J Mater Process Technol 152:333–338

    Article  Google Scholar 

  8. Davim JP, Reis P (2003) Study of delamination in drilling carbon fiber reinforced plastics (CFRP) using design experiments. Compos Struct 59:481–487

    Article  Google Scholar 

  9. Palanikumar K, Mata F, Paulo Davim J (2008) Analysis of surface roughness parameters in turning of FRP tubes by PCD tool. J Mater Process Technol 204:469–474

    Article  Google Scholar 

  10. Zadeh L (1965) Fuzzy sets. Inform Control 8:338–353

    Article  MATH  MathSciNet  Google Scholar 

  11. Raghukandan K, Hokamoto K, Manikandan P (2004) Optimization of process parameters in explosive cladding of mild steel and aluminum. Met Mater Int 10(2):193–197

    Google Scholar 

  12. Ross TJ (1992) Fuzzy logic with engineering applications, Int edn. Mc-Graw Hill, New York

  13. Poulachon G, Bandyopadhyay BP, Jawahir IS, Pheulpin S, Seguin E (2004) Wear behavior of CBN tools while turning various hardened steels. Wear 256:302–310

    Article  Google Scholar 

  14. Poulachon G, Moisan A, Jawahir IS (2001) Tool-wear mechanisms in hard turning with polycrystalline cubic boron nitride tools. Wear 250:576–586

    Article  Google Scholar 

  15. Tzeng C-J, Lin Y-H, Yang Y-K, Jeng M-C (2009) Optimization of turning operations with multiple performance characteristics using the Taguchi method and Grey relational analysis. J Mater Process Technol 209:2753–2759

    Article  Google Scholar 

  16. Chang C-W, Kuo C-P (2007) Evaluation of surface roughness in laser-assisted machining of aluminum oxide ceramics with Taguchi method. Int J Machine Tools Manuf 47:141–147

    Article  MATH  Google Scholar 

  17. Wong SV, Hamouda AMS (2000) Optimisation of fuzzy rules design using genetic algorithm. Adv Eng Softw 31:251–262

    Article  MATH  Google Scholar 

  18. Yen J, Langari R (2006) Fuzzy logic intelligence, control, and information. Dorling Kindersley Pvt Ltd, India

    Google Scholar 

  19. Nandi AK, Davim JP (2009) A study of drilling performances with minimum quantity of lubricant using fuzzy logic rules. Mechatronics 19(2):218–232

    Google Scholar 

  20. Peres CR, Guerra REH, Haber RH, Alique A, Ros S (1999) Fuzzy model and hierarchical fuzzy control integration: an approach for milling process optimization. Comput Ind 39:199–207

    Article  Google Scholar 

  21. Palanikumar K (2008) Surface roughness model for machining glass fiber reinforced plastics by PCD tool using fuzzy logics. J Reinf Plast Compos 28(18):2273–2286

    Google Scholar 

  22. Klir GJ, Folger TA (1988) Fuzzy sets, uncertainty and information. Prentice-Hall of India Private Limited, New Delhi, pp 10

  23. Sharif Ullah AMM, Harib KH (2006) A human-assisted knowledge extraction method for machining operations. Adv Eng Inform 20:335–350

    Article  Google Scholar 

  24. Jang JSR, Sun CT, Mizutani E (2004) Neuro-Fuzzy and soft computing—a computational approach to learning and machine Intelligence. Pearson Education, Pvt Ltd, Singapore, India Branch, 482 F.I.E., Patparganj, Delhi—110 092, India, pp 24–25

  25. Dixit PM, Dixit US (2008) Chapter 8 Background on soft computing. Engineering Materials and Processes, Model of Metal Forming and Machining Processes, pp 451–501

  26. Latha B, Senthilkumar VS (2009) Analysis of thrust force in drilling glass fiber-reinforced plastic composites using fuzzy logic. Mater Manuf Process 24:4, 509–516

    Google Scholar 

  27. Latha B, Senthilkumar VS (2009) Fuzzy rule based modeling of drilling parameters for delamination in drilling GFRP composites. J Reinf Plast Compos 28:951–964 (originally published)

    Google Scholar 

  28. Boothroyd G, Knight WA (1988) Fundamentals of machining and machine tools. Marcel Dekker, New York, pp 155–173

  29. Palanikumar K, Sivakumar G, Paulo Davim J (2008) Development of an empirical model for surface roughness in the machining of Al/SiC particulate composites by PCD tool. Int J Mater Prod Technol 32(2-3):318–332

    Google Scholar 

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Rajasekaran, T., Palanikumar, K. & Vinayagam, B.K. Application of fuzzy logic for modeling surface roughness in turning CFRP composites using CBN tool. Prod. Eng. Res. Devel. 5, 191–199 (2011). https://doi.org/10.1007/s11740-011-0297-y

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