Abstract
A fuzzy decision-making approach was developed to optimize laser-assisted joining process of polymer-metal hybrid structures. A systematic approach based on Design of Experiment was adopted to identify and explain the effect of each process parameter, i.e. laser energy and laser power, on the response variables, i.e. maximum operating temperature and shear strength. Then, a combined fuzzy-genetic algorithm model was developed to find the best input parameters’ combination capable to satisfy the requirement of the best processing performances, in terms of appropriate range of operating temperature and highest shear strength. The use of genetic algorithms involved the choice of the best nominal regression model and the optimisation of the fuzzy numbers. This enabled to account most of the experimental data in combination with the smallest uncertainty level. Experimental results showed the success of the joining process ensuring sufficient adhesion of the hybrid structure over time, with shear strength of almost 29 MPa by using a laser power of 150 W and energy of 2 kJ. Moreover, the fuzzy process maps enable the selection of the process parameters with the aim of achieving desired process output along with the lowest uncertainty level. In addition, it also provides the amount of uncertainty of the model. The results indicated that a low laser energy level of 2250 J and a laser power in the range 120–140 W would provide the optimal solution in terms of operating temperature (i.e. between 343 and 520 °C), shear strength (i.e. greater than 26 MPa) and uncertainty level (i.e. membership level greater than 0.9).
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References
Lambiase F, Genna S (2018) Laser assisted joining of AA5053 aluminum alloy with polyvinyl chloride (PVC). Opt Laser Technol 107:80–88. https://doi.org/10.1016/j.optlastec.2018.05.023
Troughton MJ (ed) (2009) Mechanical fastening. In: Handbook of Plastics Joining, Second edn. Elsevier, pp 175–201. https://doi.org/10.1016/B978-0-8155-1581-4.50020-2
Oplinger DW (1998) Mechanical fastening and adhesive bonding. In: Handbook of Composites. Springer, Boston, pp 610–666. https://doi.org/10.1007/978-1-4615-6389-1_29
Kweon J-H, Jung J-W, Kim T-H, Choi J-H, Kim D-H (2006) Failure of carbon composite-to-aluminum joints with combined mechanical fastening and adhesive bonding. Compos Struct 75:192–198. https://doi.org/10.1016/j.compstruct.2006.04.013
Huang Y, Meng X, Wang Y, Xie Y, Zhou L (2018) Joining of aluminum alloy and polymer via friction stir lap welding. J Mater Process Technol 257:148–154. https://doi.org/10.1016/j.jmatprotec.2018.02.043
Lambiase F, Paoletti A, Grossi V, Di Ilio A (2017) Friction assisted joining of aluminum and PVC sheets. J Manuf Process 29:221–231. https://doi.org/10.1016/j.jmapro.2017.07.026
Huang Y, Meng X, Xie Y, Li J, Wan L (2019) New technique of friction-based filling stacking joining for metal and polymer. Compos Part B Eng 163:217–223. https://doi.org/10.1016/j.compositesb.2018.11.050
Frick T, Schkutow A (2018) Laser transmission welding of polymers – irradiation strategies for strongly scattering materials. Procedia CIRP 74:538–543. https://doi.org/10.1016/j.procir.2018.08.118
Chatterjee S, Mahapatra SS, Bharadwaj V, Upadhyay BN, Bindra KS, Thomas J (2019) Parametric appraisal of mechanical and metallurgical behavior of butt welded joints using pulsed Nd:YAG laser on thin sheets of AISI 316. Opt Laser Technol 117:186–199. https://doi.org/10.1016/j.optlastec.2019.04.004
Engelmann C, Eckstaedt J, Olowinsky A, Aden M, Mamuschkin V (2016) Experimental and simulative investigations of laser assisted plastic-metal-joints considering different load directions. Phys Procedia 83:1118–1129. https://doi.org/10.1016/j.phpro.2016.08.117
Rodríguez-Vidal E, Sanz C, Lambarri J, Quintana I (2018) Experimental investigation into metal micro-patterning by laser on polymer-metal hybrid joining. Opt Laser Technol 104:73–82. https://doi.org/10.1016/J.OPTLASTEC.2018.02.003
Chueh Y-H, Wei C, Zhang X, Li L (2020) Integrated laser-based powder bed fusion and fused filament fabrication for three-dimensional printing of hybrid metal/polymer objects. Addit Manuf 31:100928. https://doi.org/10.1016/J.ADDMA.2019.100928
Ozlati A, Movahedi M, Tamizi M, Tartifzadeh Z, Alipour S (2019) An alternative additive manufacturing-based joining method to make metal/polymer hybrid structures. J Manuf Process 45:217–226. https://doi.org/10.1016/J.JMAPRO.2019.07.002
Ponticelli GS, Lambiase F, Leone C, Genna S (2020) Combined fuzzy and genetic algorithm for the optimisation of hybrid composite-polymer joints obtained by two-step laser joining process. Materials (Basel) 13:283. https://doi.org/10.3390/ma13020283
Rao RV (2007) Decision making in the manufacturing environment: using graph theory and fuzzy multiple attribute decision making methods. In: Springer Series in Advanced Manufacturing, First edn. Springer London Ltd, pp 3–5
Abhishek K, Chatterjee S, Datta S, Mahapatra SS (2017) Integrating principal component analysis, fuzzy linguistic reasoning and Taguchi philosophy for quality-productivity optimization. Mater Today Proc 4:1772–1777. https://doi.org/10.1016/j.matpr.2017.02.019
Elishakoff I, Ferracuti B (2006) Four alternative definitions of the fuzzy safety factor. J Aerosp Eng 19:281–287. https://doi.org/10.1061/(ASCE)0893-1321(2006)19:4(281)
Guarino S, Ponticelli GS (2017) High power diode laser (HPDL) for fatigue life improvement of steel: numerical modelling. Metals (Basel) 7. https://doi.org/10.3390/met7100447
Chatterjee S, Mahapatra SS, Mondal A, Abhishek K (2018) An experimental study on drilling of titanium alloy using CO2 laser. Sadhana - Acad Proc Eng Sci 43:131. https://doi.org/10.1007/s12046-018-0903-1
Lambiase F, Genna S, Kant R (2018) Optimization of laser-assisted joining through an integrated experimental-simulation approach. Int J Adv Manuf Technol 97:2655–2666. https://doi.org/10.1007/s00170-018-2113-8
Lambiase F, Genna S, Kant R (2018) A procedure for calibration and validation of FE modelling of laser-assisted metal to polymer direct joining. Opt Laser Technol 98:363–372. https://doi.org/10.1016/j.optlastec.2017.08.016
Chatterjee S, Mahapatra SS, Bharadwaj V, Choubey A, Upadhyay BN, Bindra KS (2019) Drilling of micro-holes on titanium alloy using pulsed Nd:YAG laser: parametric appraisal and prediction of performance characteristics. Proc Inst Mech Eng Part B J Eng Manuf 233:1872–1889. https://doi.org/10.1177/0954405418805604
Coroiu AM (2015) Fuzzy methods in decision making process - a particular approach in manufacturing systems. IOP Conf Ser Mater Sci Eng 95:012154. https://doi.org/10.1088/1757-899X/95/1/012154
Yusoff N, Anamul Hossain KM, Altab Hossain M, Parandoush P, Mohammed Sifullah A (2014) Fuzzy Logic Modeling of Silicon Nitride (Si3N4) Laser Cutting. Aust J Basic Appl Sci 8:7–11
Ponticelli GS, Guarino S, Giannini O (2018) A fuzzy logic-based model in laser-assisted bending springback control. Int J Adv Manuf Technol 95:3887–3898. https://doi.org/10.1007/s00170-017-1482-8
Ponticelli GS, Guarino S, Tagliaferri V, Giannini O (2019) An optimized fuzzy-genetic algorithm for metal foam manufacturing process control. Int J Adv Manuf Technol 101:603–614. https://doi.org/10.1007/s00170-018-2942-5
Zadeh LA (1965) Fuzzy Sets. Inf Control 8:338–353
Rodger JA (2014) Application of a fuzzy feasibility Bayesian probabilistic estimation of supply chain backorder aging, unfilled backorders, and customer wait time using stochastic simulation with Markov blankets. Expert Syst Appl 41:7005–7022. https://doi.org/10.1016/j.eswa.2014.05.012
Salicone S (2007) Measurement uncertainty. Boston, Springer. https://doi.org/10.1007/978-0-387-46328-5
Lambiase F, Genna S (2018) Experimental analysis of laser assisted joining of Al-Mg aluminium alloy with polyetheretherketone (PEEK). Int J Adhes Adhes 84:265–274. https://doi.org/10.1016/j.ijadhadh.2018.04.004
Zorko D, Kulovec S, Duhovnik J, Tavčar J (2019) Durability and design parameters of a steel/PEEK gear pair. Mech Mach Theory 140:825–846. https://doi.org/10.1016/j.mechmachtheory.2019.07.001
Lambiase F, Paoletti A, Grossi V, Genna S (2017) Improving energy efficiency in friction assisted joining of metals and polymers. J Mater Process Technol 250:379–389. https://doi.org/10.1016/j.jmatprotec.2017.08.005
Montgomery DC (1991) Design and analysis of experiments. Wiley, Chichester
Acherjee B, Kuar AS, Mitra S, Misra D (2015) Laser transmission welding of polycarbonates: experiments, modeling, and sensitivity analysis. Int J Adv Manuf Technol 78:853–861. https://doi.org/10.1007/s00170-014-6693-7
Liu H, Wang K, Li P, Zhang C, Du D, Hu Y et al (2012) Modeling and prediction of transmission laser bonding process between titanium coated glass and PET based on response surface methodology. Opt Lasers Eng 50:440–448. https://doi.org/10.1016/j.optlaseng.2011.10.010
Verotti M, Di Giamberardino P, Belfiore NP, Giannini O (2019) A genetic algorithm-based method for the mechanical characterization of biosamples using a MEMS microgripper: numerical simulations. J Mech Behav Biomed Mater 96:88–95. https://doi.org/10.1016/j.jmbbm.2019.04.023
Dumont-Fillon D, Hannebelle M, Van Lintel H, Chappel E (2016) Design of a passive flow regulator using a genetic algorithm. Procedia Eng 168:1016–1019. https://doi.org/10.1016/j.proeng.2016.11.329
Alberdi R, Khandelwal K (2015) Comparison of robustness of metaheuristic algorithms for steel frame optimization. Eng Struct 102:40–60. https://doi.org/10.1016/j.engstruct.2015.08.012
Dao SD, Abhary K, Marian R (2017) A bibliometric analysis of genetic algorithms throughout the history. Comput Ind Eng 110:395–403. https://doi.org/10.1016/j.cie.2017.06.009
Alimardani M, Toyserkani E (2008) Prediction of laser solid freeform fabrication using neuro-fuzzy method. Appl Soft Comput 8:316–323. https://doi.org/10.1016/j.asoc.2007.02.002
Hanss M (2002) The transformation method for the simulation and analysis of systems with uncertain parameters. Fuzzy Sets Syst 130:277–289
Hanss M (2005) Applied fuzzy arithmetic: an introduction with engineering applications, Springer-Verlag, pp 99–126
Ismail H (2018) Statistical modeling, linear regression and ANOVA, a practical computational perspective. Lulu.com, pp 466
Miller RG, Brown BW (1997) Beyond ANOVA: basics of applied statistics. First edn. Chapman & Hall/CRC, pp 164–240
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Genna, S., Lambiase, F. & Ponticelli, G.S. Fuzzy decision-making in laser-assisted joining of polymer-metal hybrid structures. Int J Adv Manuf Technol 108, 61–72 (2020). https://doi.org/10.1007/s00170-020-05379-7
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DOI: https://doi.org/10.1007/s00170-020-05379-7