Abstract
Laser transmission welding is a quick, easy, and viable method to join plastic materials for several industrial domains. The main challenge for manufacturers is still on how to choose the input process parameters to achieve the best joint performance. Joining between PET (polyethylene terephthalate) films does not make an exception, with quality strictly depending on laser joining parameters. The purpose of the present study is to estimate the weldability of a polymeric material couple according to their thermal and optical properties. This paper investigates an experimental study of laser transmission welding of PET 100% and PET-PEVA (polyethylene vinyl acetate) 5%, 10%, and 15% sheets by a diode laser. In the present work, laser power and scan speed were considered as operational parameters, which have a significant influence on the quality of the joint zone. Then, the influence of PEVA aliquots in PET/PEVA blends, which altered the mechanical properties, such as joining behavior, mechanical characterization, and degradation level, was analyzed. In addition, an artificial neural network model is developed to achieve the optimal laser parameters. The obtained results proved the advantage of this model, as a prediction tool, for developing laser welding parameters.
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References
Speka M, Matteï S, Pilloz M, Ilie M (2008) The infrared thermography control of the laser welding of amorphous polymers. NDT&E Int 41:178–183
Zak G, Mayboudi L, Chen M, Bates PJ, Birk M (2010) Weld line transverse energy density distribution measurement in laser transmission welding of thermoplastics. J Mater Process Technol 210:24–31
Gisario A, Veniali F, Barletta M, Tagliaferri V, Vesco S (2017) Laser transmission welding of poly (ethylene terephthalate) and biodegradable poly (ethylene terephthalate)–based blends. Opt Lasers Eng 90:110–118
Brown N, Kerr D, Jackson M, Parkin R (2000) Laser welding of thin polymer films to container substrates for aseptic packaging. Opt Laser Technol 32:139–146
Gisario A, Mehrpouya M, Pizzi E (2017) Dissimilar joining of transparent poly (ethylene terephthalate) to aluminum 7075 sheets using a diode laser. J Laser Appl 29:022418
Coelho J, Abreu M, Pires M (2000) High-speed laser welding of plastic films. Opt Lasers Eng 34:385–395
Mehrpouya M, Lavvafi H, and Darafsheh A (2018) "Microstructural characterization and mechanical reliability of laser-machined structures," in Advances in laser materials processing (second Edition), ed: Elsevier, pp. 731–761
Gisario A, Barletta M, Venettacci S, Veniali F (2015) External force-assisted LaserOrigami (LO) bending: shaping of 3D cubes and edge design of stainless steel chairs. J Manuf Process 18:159–166
Gisario A, Mehrpouya M, Venettacci S, Barletta M (2017) Laser-assisted bending of titanium Grade-2 sheets: experimental analysis and numerical simulation. Opt Lasers Eng 92:110–119
von Bülow JF, Bager K, Thirstrup C (2009) Utilization of light scattering in transmission laser welding of medical devices. Appl Surf Sci 256:900–908
Geiger M, Frick T, Schmidt M (2009) Optical properties of plastics and their role for the modelling of the laser transmission welding process. Prod Eng 3:49–55
Mayboudi L, Birk A, Zak G, and Bates P (2006) "Thermal imaging studies and 3-D thermal finite element modeling of laser transmission welding of a lap-joint," in ASME 2006 international mechanical engineering congress and exposition, pp. 423–432
Mehrpouya M, Gisario A, Brotzu A, Natali S (2018) Laser welding of NiTi shape memory sheets using a diode laser. Opt Laser Technol 108C:142–149
Ilie M, Cicala E, Grevey D, Mattei S, Stoica V (2009) Diode laser welding of ABS: experiments and process modeling. Opt Laser Technol 41:608–614
Ilie M, Kneip J-C, Matteï S, Nichici A, Roze C, Girasole T (2007) Through-transmission laser welding of polymers–temperature field modeling and infrared investigation. Infrared Phys Technol 51:73–79
Ussing T, Petersen L, Nielsen C, Helbo B, Højslet L (2007) Micro laser welding of polymer microstructures using low power laser diodes. Int J Adv Manuf Technol 33:198–205
Amanat N, Chaminade C, Grace J, McKenzie DR, James NL (2010) Transmission laser welding of amorphous and semi-crystalline poly-ether–ether–ketone for applications in the medical device industry. Mater Des 31:4823–4830
Chen M, Zak G, Bates PJ (2011) Effect of carbon black on light transmission in laser welding of thermoplastics. J Mater Process Technol 211:43–47
Sterjovski Z, Nolan D, Carpenter K, Dunne D, Norrish J (2005) Artificial neural networks for modelling the mechanical properties of steels in various applications. J Mater Process Technol 170:536–544
LM L, ML Z, JT N, ZD Z (2001) Predicting effects of diffusion welding parameters on welded joint properties by artificial neural network. Trans Nonferrous Metals Soc China (Eng Ed) 11:475–478
Jeng J-Y, Mau T-F, Leu S-M (2000) Prediction of laser butt joint welding parameters using back propagation and learning vector quantization networks. J Mater Process Technol 99:207–218
Acherjee B, Mondal S, Tudu B, Misra D (2011) Application of artificial neural network for predicting weld quality in laser transmission welding of thermoplastics. Appl Soft Comput 11:2548–2555
Wang X, Zhang C, Li P, Wang K, Hu Y, Zhang P, Liu H (2012) Modeling and optimization of joint quality for laser transmission joint of thermoplastic using an artificial neural network and a genetic algorithm. Opt Lasers Eng 50:1522–1532
Naumetc D (2017) "Building the artificial neural network environment: artificial neural networks in plane control,"
Karlik B, Olgac AV (2011) Performance analysis of various activation functions in generalized MLP architectures of neural networks. Int J Artif Intell Expert Syst 1:111–122
Lipton ZC, Berkowitz J, and Elkan C (2015) "A critical review of recurrent neural networks for sequence learning," arXiv preprint arXiv:1506.00019
Broomhead DS and Lowe D (1988) "Radial basis functions, multi-variable functional interpolation and adaptive networks," Royal Signals and Radar Establishment Malvern (United Kingdom)
Aguilar DP (2004) "A radial basis neural network for the analysis of transportation data,"
Rumelhart DE, Hinton GE, Williams RJ (1986) Learning representations by back-propagating errors. nature 323:533–536
Schmidhuber J (2015) Deep learning in neural networks: an overview. Neural Netw 61:85–117
Burrascano P, Fiori S, Mongiardo M (1999) A review of artificial neural networks applications in microwave computer-aided design (invited article). Int J RF Microwave Comput Aided Eng 9:158–174
Mirjalili S, Mirjalili SM, Lewis A (2014) Let a biogeography-based optimizer train your multi-layer perceptron. Inf Sci 269:188–209
Guresen E, Kayakutlu G (2011) Definition of artificial neural networks with comparison to other networks. Procedia Comput Sci 3:426–433
Grewell D, Benatar A (2007) Welding of plastics: fundamentals and new developments. Int Polym Process 22:43–60
Kang M, Jeon I-H, Han HN, Kim C (2018) Tensile–shear fracture behavior prediction of high-strength steel laser overlap welds. Metals 8:365
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Mehrpouya, M., Gisario, A., Rahimzadeh, A. et al. An artificial neural network model for laser transmission welding of biodegradable polyethylene terephthalate/polyethylene vinyl acetate (PET/PEVA) blends. Int J Adv Manuf Technol 102, 1497–1507 (2019). https://doi.org/10.1007/s00170-018-03259-9
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DOI: https://doi.org/10.1007/s00170-018-03259-9