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A fuzzy logic-based prediction model for fracture force using low-power fiber laser beam welding

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Abstract

Laser beam welding is an advanced technique to join dissimilar materials together. Important laser joining parameters such as laser power, welding speed, and overlapping factor would determine the weld penetration of the joints. In the current study, a single-sided welding of a titanium alloy, Ti6Al4V, and a nickel-based alloy, Inconel 600, in a T-joint configuration was conducted using a continuous-wave, low-power fiber laser. The strengths of the welded joints were evaluated using pull tests. These results were used to build an intelligent fuzzy expert system model to predict the fracture force of the joint. Using MATLAB R2009b, the fuzzy logic development was made based on the Mamdani technique. Twenty-four real-time experiments were carried out and 18 numerical testing data were used to develop the fuzzy logic. The resulting viewer surfaces showed that the overlapping factor was the highest influencing laser welding parameter, followed by the welding speed and the laser power. The calculated relative error between the real and predicted results was 6.95% indicating acceptable results. This was supported by the goodness of fit value of 0.9849. The findings of this study have extended the knowledge of the fracture force prediction using the fuzzy expert system model.

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Reference

  1. Janasekaran S, Jamaludin MF, Muhamad MR, Yusof F, Shukor MHA (2016) Autogenous double-sided T-joint welding on aluminum alloys using low power fiber laser. Int J Adv Manuf Technol:1–9

  2. Janasekaran S, Tan AW, Yusof F, Abdul Shukor M (2016) Feasibility study of low power fiber laser welding AA2024 and AA7075 alloys T-joint. Key Eng Mater 701:182–186

    Article  Google Scholar 

  3. Guo JF, Chen HC, Sun CN, Bi G, Sun Z, Wei J (2014) Friction stir welding of dissimilar materials between AA6061 and AA7075 Al alloys effects of process parameters. Mater Des 56:185–192

    Article  Google Scholar 

  4. Farazila Y, Miyashita Y, Hua W, Mutoh Y, Otsuka Y (2011) YAG laser spot welding of PET and metallic materials. J Laser Micro Nanoen 6(1):69–74. doi:10.2961/jlmn.2011.01.0015

    Article  Google Scholar 

  5. Shen Y, Liu Y, Sun W, Dong H, Zhang Y, Wang X, Zheng C, Ji R (2015) High-speed dry compound machining of Ti6Al4V. J Mater Process Tech 224:200–207

    Article  Google Scholar 

  6. Shokrani A, Dhokia V, Newman ST (2012) Environmentally conscious machining of difficult-to-machine materials with regard to cutting fluids. International Journal of Machine Tools & Manufacture 57:83–101

    Article  Google Scholar 

  7. Chen HC, Pinkerton AJ, Li L (2011) Fibre laser welding of dissimilar alloys of Ti-6Al-4V and Inconel 718 for aerospace applications. Int J Adv Manuf Tech 52(9–12):977–987. doi:10.1007/s00170-010-2791-3

    Article  Google Scholar 

  8. Mavrigian M (2014) Performance exhaust systems: how to design, fabricate, and install. CarTech Inc

  9. MPR (2012) Off to the races. Metal Powder Report, vol 67. Elsevier Ltd

  10. Vince (2015) Welding exhaust systems—Part 1. Burns Stainless. Burns Stainless, USA

  11. Tarng YS, Yang WH (1998) Optimisation of the weld bead geometry in gas tungsten arc welding by the Taguchi method. Int J Adv Manuf Technol 14(8):549–554. doi:10.1007/bf01301698

    Article  Google Scholar 

  12. Stares IJ, Duffil C, Ogilvy JA, Scruby CB (1990) On-line weld pool monitoring and defect detection using ultrasonic. NDT Int 23(4):195–200. doi:10.1016/0308-9126(90)91601-O

    Google Scholar 

  13. Kurakake Y, Farazila Y, Miyashita Y, Otsuka Y, Mutoh Y (2013) Effect of molten pool shape on tensile shear strength of dissimilar materials laser spot joint between plastic and metal. Journal of Laser Micro/Nanoengineering 8(2):161–164

    Article  Google Scholar 

  14. Tadamalle A, Reddy Y, Ramjee E (2013) Optimization of Nd: YAG laser welding process parameters for dissimilar metals. In: IWW, international conference, pp 8–10

  15. Nath AK, Sridhar R, Ganesh P, Kaul R (2002) Laser power coupling efficiency in conduction and keyhole welding of austenitic stainless steel. Sadhana-Acad P Eng S 27:383–392. doi:10.1007/Bf02703659

    Article  Google Scholar 

  16. Benyounis KY, Olabi AG, Hashmi MSJ (2005) Effect of laser welding parameters on the heat input and weld-bead profile. J Mater Process Tech 164-165:978–985. doi:10.1016/j.jmatprotec.2005.02.060

    Article  Google Scholar 

  17. Tadamalle A, Reddy Y, Ramjee E (2013) Influence of laser welding process parameters on weld pool geometry and duty cycle. Advances in Production Engineering & Management 8(1):52

    Article  Google Scholar 

  18. Balasubramanian K, Buvanashekaran G, Sankaranarayanasamy K (2010) Modeling of laser beam welding of stainless steel sheet butt joint using neural networks. CIRP J Manuf Sci Technol 3(1):80–84

    Article  Google Scholar 

  19. Pan LK, Wang CC, Hsiao YC, Ho KC (2005) Optimization of Nd: YAG laser welding onto magnesium alloy via Taguchi analysis. Optics & Laser Technology 37(1):33–42. doi:10.1016/j.optlastec.2004.02.007

    Article  Google Scholar 

  20. Zhang YM, Kovacevic R, Li L (1996) Characterization and real-time measurement of geometrical appearance of the weld pool. Int J Mach Tools Manuf 36(7):799–816. doi:10.1016/0890-6955(95)00083-6

    Article  Google Scholar 

  21. Sathiya P, Jaleel MYA, Katherasan D, Shanmugarajan B (2011) Optimization of laser butt welding parameters based on the orthogonal array with fuzzy logic and desirability approach. Struct Multidiscip O 44(4):499–515. doi:10.1007/s00158-010-0615-6

    Article  Google Scholar 

  22. Kumar A, Maheshwari S, Sharma SK (2015) Fuzzy logic optimization of weld properties for SAW using silica based agglomerated flux. Procedia Computer Science 57:1140–1148. doi:10.1016/j.procs.2015.07.403

    Article  Google Scholar 

  23. Surender Y, Pratihar DK (2013) Fuzzy logic-based techniques for modeling the correlation between the weld bead dimension and the process parameters in MIG welding. International Journal of Manufacturing Engineering 2013

  24. Austin MA, Dunne KC, Lindland D, Frey PL, Hystad DG, Nelson RE, Warner BD (1997) Welding control using fuzzy logic analysis of video imaged puddle dimensions. Google Patents

  25. Aghakhani M, Jalilian MM, Karami A (2012) Prediction of weld bead dilution in GMAW process using fuzzy logic. In: Applied mechanics and materials. Trans Tech Publ, pp 3171–3175

  26. Kuo H-C, Wu L-J (2002) An image tracking system for welded seams using fuzzy logic. J Mater Process Tech 120(1):169–185

    Article  Google Scholar 

  27. Ganjigatti J, Pratihar DK (2008) Forward and reverse modeling in MIG welding process using fuzzy logic-based approaches. Journal of Intelligent & Fuzzy Systems 19(2):115–130

    Google Scholar 

  28. Badini C, Pavese M, Fino P, Biamino S (2009) Laser beam welding of dissimilar aluminium alloys of 2000 and 7000 series: effect of post-welding thermal treatments on T joint strength. Sci Technol Weld Joi 14(6):484–492. doi:10.1179/136217108x372559

    Article  Google Scholar 

  29. Janasekaran S, Tan A, Yusof F, Abdul Shukor M (2016) Influence of the overlapping factor and welding speed on T-joint welding of Ti6Al4V and Inconel 600 using low-power fiber laser. Metals 6(6):134

    Article  Google Scholar 

  30. Ross TJ (2009) Fuzzy logic with engineering applications. Wiley, New York

    Google Scholar 

  31. Pedrycz W (1994) Why triangular membership functions? Fuzzy Sets Syst 64(1):21–30. doi:10.1016/0165-0114(94)90003-5

    Article  MathSciNet  Google Scholar 

  32. Klir GJ, Yuan B (1995) Fuzzy sets and fuzzy logic: theory and applications. Prentice Hall PTR, Upper Saddle River, NJ

    MATH  Google Scholar 

  33. Kumar S, Datta D, Sharma S, Chourasiya G, Babu D, Sharma D (2014) Estimation of distance error by fuzzy set theory required for strength determination of HDR 192Ir brachytherapy sources. Journal of medical physics/Association of Medical Physicists of India 39(2):85

    Google Scholar 

  34. Rajasekaran S, Pai GAV (2003) Neural networks, fuzzy logic and genetic algorithm: synthesis and applications. PHI Learning

  35. Hossain A, Hossain A, Nukman Y, Hassan MA, Harizam MZ, Sifullah AM, Parandoush P (2016) A fuzzy logic-based prediction model for kerf width in laser beam machining. Mater Manuf Process 31(5):679–684. doi:10.1080/10426914.2015.1037901

    Article  Google Scholar 

  36. Unt A, Salminen A (2015) Effect of welding parameters and the heat input on weld bead profile of laser welded T-joint in structural steel. J Laser Appl 27. doi:Artn S29002 doi:10.2351/1.4906378

  37. Ribic B, Palmer TA, DebRoy T (2009) Problems and issues in laser-arc hybrid welding. Int Mater Rev 54(4):223–244. doi:10.1179/174328009x411163

    Article  Google Scholar 

  38. Gao X-L, Liu J, Zhang L-J, Zhang J-X (2014) Effect of the overlapping factor on the microstructure and mechanical properties of pulsed Nd: YAG laser welded Ti6Al4V sheets. Mater Charact 93:136–149. doi:10.1016/j.matchar.2014.04.005

    Article  Google Scholar 

  39. Nukman Y, Hassan MA, Harizam MZ (2013) Optimization of prediction error in CO2 laser cutting process by Taguchi artificial neural network hybrid with genetic algorithm. Applied Mathematics & Information Sciences 7(1):363–370

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia

    Shamini Janasekaran, Farazila Yusof, Harizam Mohd Zin & Mohd Hamdi Abdul Shukor

  2. Centre of Advanced Manufacturing and Material Processing (AMMP), Lingkungan Budi, University of Malaya, Kuala Lumpur, Malaysia

    Farazila Yusof, Mohd Fadzil Jamaludin & Mohd Hamdi Abdul Shukor

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  1. Shamini Janasekaran
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  2. Farazila Yusof
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  3. Harizam Mohd Zin
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  4. Mohd Fadzil Jamaludin
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  5. Mohd Hamdi Abdul Shukor
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Correspondence to Shamini Janasekaran.

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Janasekaran, S., Yusof, F., Zin, H.M. et al. A fuzzy logic-based prediction model for fracture force using low-power fiber laser beam welding. Int J Adv Manuf Technol 91, 3603–3610 (2017). https://doi.org/10.1007/s00170-017-0073-z

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  • DOI: https://doi.org/10.1007/s00170-017-0073-z

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