Abstract
Laser shock hole-clinching is one of mechanical joining processes in which metal foils are joined together based on plastic deformation caused by laser-induced shock wave. In the process, fracture often occurs due to the unreasonable arrangement of laser process parameters, suggesting that it is urgent to seek a feasible way to improve the joint forming quality. However, it consumes a great deal of time and effort to obtain the optimal solution of process parameters from so many different combinations through experiments and numerical simulations. In this study, the mathematical models between laser process parameters and joint forming quality were established through response surface methodology (RSM). A finite element analysis model of laser shock hole-clinching process for pure copper and pre-pierced stainless steel foils was developed, and then it was used to perform the calculation scheme arranged by design of experiments. Analysis of variance (ANOVA) was implemented to evaluate the statistical significance of RSM models and the influence of process parameters on objectives. Multi-objective optimization was carried out to achieve the optimal combination of laser process parameters by using genetic algorithm (GA). It is revealed that the RSM-GA-integrated approach is an effective way to realize the modeling and optimization of laser process parameters for laser shock hole-clinching. The pulsed laser energy (E), number of laser pulses (N), and laser spot diameter (D) are statistically significant, and both the interlock value and the maximum thinning rate are sensitive to these parameters based on ANOVA. The fitting precision analysis indicates that the established RSM models can be used to navigate the design space of variables and predict the actual data with high accuracy. Moreover, it is found that the influence order of laser process parameters on the interlock value from strong to weak is N, E, and D, while this order changes to D, N, and E for the maximum thinning rate. According to the Pareto noninferior solutions and the corresponding values of satisfaction function, the optimal combination is E = 164 mJ, N = 25, and D = 2.1 mm in the given design space. The GA optimization result has been experimentally confirmed.
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References
Righi G, Ruestes CJ, Stan CV, Ali SJ, Rudd RE, Kawasaki M, Park HS, Meyers MA (2021) Towards the ultimate strength of iron: spalling through laser shock. Acta Mater 215:117072. https://doi.org/10.1016/j.actamat.2021.117072
Groche P, Wohletz S, Brenneis M, Pabst C, Resch F (2014) Joining by forming—a review on joint mechanisms, applications and future trends. J Mater Process Technol 214:1972–1994. https://doi.org/10.1016/j.jmatprotec.2013.12.022
Wang XY, Ji Z, Liu R, Zheng C (2018) Making interlock by laser shock forming. Opt Laser Technol 107:331–336. https://doi.org/10.1016/j.optlastec.2018.06.011
Veenaas S, Wielage H, Vollertsen F (2014) Joining by laser shock forming: realization and acting pressures. Prod Eng Res Devel 8:283–290. https://doi.org/10.1007/s11740-013-0521-z
Wang X, Li XD, Li C, Shen ZB, Ma YJ, Liu HX (2018) Laser shock micro clinching of Al/Cu. J Mater Process Technol 258:200–210. https://doi.org/10.1016/j.jmatprotec.2018.04.005
Li XD, Wang X, Shen ZB, Ma YJ, Liu HX (2019) An experimental study on micro-shear clinching of metal foils by laser shock. Materials 12:1422. https://doi.org/10.3390/ma12091422
Wang J, Wang YQ, Wang S, Lu GX, Zheng C, Ji Z (2021) Experimental and numerical investigation on incremental laser shock clinching for joining three sheets of copper/aluminum/stainless steel. Opt Laser Technol 141:107141. https://doi.org/10.1016/j.optlastec.2021.107141
Veenaas S, Vollertsen F (2015) Forming behavior during joining by laser induced shock waves. Key Eng Mater 651–653:1451–1456. https://doi.org/10.4028/www.scientific.net/KEM.651-653.1451
Zheng C, Pan CD, Tian ZR, Zhao XH, Zhao GQ, Ji Z, Song LB (2020) Laser shock induced incremental forming of pure copper foil and its deformation behavior. Opt Laser Technol 121:105785. https://doi.org/10.1016/j.optlastec.2019.105785
Wang XY, Ji Z, Wang JF, You SX, Zheng C, Liu R (2018) An experimental and numerical study on laser shock clinching for joining copper foil and perforated stainless steel sheet. J Mater Process Technol 258:155–164. https://doi.org/10.1016/j.jmatprotec.2018.03.025
You SX, Wang XY, Ji Z, Zheng C, Zhang GF, Liu R (2019) Making line undercut structure by incremental laser shock forming. Int J Precis Eng Manuf 20:1289–1296. https://doi.org/10.1007/s12541-019-00141-w
Lambiase F, Di Ilio A (2013) Optimization of the clinching tools by means of integrated FE modeling and artificial intelligence techniques. Procedia CIRP 12:163–168. https://doi.org/10.1016/j.procir.2013.09.029
Shen XJ, Shukla P, Subramaniyan AK, Zammit A, Swanson P, Lawrence J, Fitzpatrick ME (2020) Residual stresses induced by laser shock peening in orthopaedic Ti-6Al-7Nb alloy. Opt Laser Technol 131:106446. https://doi.org/10.1016/j.optlastec.2020.106446
Wang C, Li KF, Hu XY, Yang HT, Zhou YJ (2021) Numerical study on laser shock peening of TC4 titanium alloy based on the plate and blade model. Opt Laser Technol 142:107163. https://doi.org/10.1016/j.optlastec.2021.107163
Wu JJ, Xu ZH, Qiao HC, Zhao JB, Huang Z (2021) Mechanical properties prediction of superalloy FGH4095 treated by laser shock processing based on machine learning. Mater Lett 297:129970. https://doi.org/10.1016/j.matlet.2021.129970
Davidson MJ, Balasubramanian K, Tagore GRN (2008) Surface roughness prediction of flow-formed AA6061 alloy by design of experiments. J Mater Process Technol 202:41–46. https://doi.org/10.1016/j.jmatprotec.2007.08.065
Bagudanch I, Vives-Mestres M, Sabater M, Garcia-Romeu ML (2017) Polymer incremental sheet forming process: temperature analysis using response surface methodology. Mater Manuf Processes 32:44–53. https://doi.org/10.1080/10426914.2016.1176191
Mostafanezhad H, Menghari HG, Esmaeili S, Shirkharkolaee EM (2018) Optimization of two-point incremental forming process of AA1050 through response surface methodology. Measurement 127:21–28. https://doi.org/10.1016/j.measurement.2018.04.042
Chen C, Zhao SD, Han XL, Cui MC, Fan SQ (2016) Optimization of a reshaping rivet to reduce the protrusion height and increase the strength of clinched joints. J Mater Process Technol 234:1–9. https://doi.org/10.1016/j.jmatprotec.2016.03.006
Eshtayeh M, Hrairi M (2016) Multi objective optimization of clinching joints quality using Grey-based Taguchi method. Int J Adv Manuf Technol 87:233–249. https://doi.org/10.1007/s00170-016-8471-1
Roux E, Bouchard PO (2013) Kriging metamodel global optimization of clinching joining processes accounting for ductile damage. J Mater Process Technol 213:1038–1047. https://doi.org/10.1016/j.jmatprotec.2013.01.018
Oudjene M, Ben-Ayed L, Delamézière A, Batoz JL (2009) Shape optimization of clinching tools using the response surface methodology with moving least-square approximation. J Mater Process Technol 209:289–296. https://doi.org/10.1016/j.jmatprotec.2008.02.030
Wang MH, Xiao GQ, Li Z, Wang JQ (2018) Shape optimization methodology of clinching tools based on Bezier curve. Int J Adv Manuf Technol 94:2267–2280. https://doi.org/10.1007/s00170-017-0987-5
Schwarz C, Kropp T, Kraus C, Drossel W (2020) Optimization of thick sheet clinching tools using principal component analysis. Int J Adv Manuf Technol 106:471–479. https://doi.org/10.1007/s00170-019-04512-5
Fabbro R, Fournier J, Ballard P, Devaux D, Virmont J (1990) Physical study of laser-produced plasma in confined geometry. J Appl Phys 68:775–784. https://doi.org/10.1063/1.346783
Zhang WW, Yao YL (2002) Microscale laser shock processing of metallic components. J Manuf Sci Eng 124:369–378. https://doi.org/10.1115/1.1445149
Wielage H, Vollertsen F (2011) Classification of laser shock forming within the field of high speed forming processes. J Mater Process Technol 211:953–957. https://doi.org/10.1016/j.jmatprotec.2010.07.012
Johnson GR, Cook WH (1983) A constitutive model and data for metals subjected to large strains, high strain rates and high temperatures, 7th International Symposium on Ballistics. Hague, Netherlands, pp 541–547
Zheng C, Sun S, Ji Z, Wang W, Liu J (2010) Numerical simulation and experimentation of micro scale laser bulge forming. Int J Mach Tools Manuf 50:1048–1056. https://doi.org/10.1016/j.ijmachtools.2010.08.012
Myers RH, Montgomery DC, Anderson-Cook CM (2016) Response surface methodology: process and product optimization using designed experiments, 4th edn. Wiley, New Jersey
Fenske H, Vollertsen F (2019) Laser shock punching: principle and influencing factors. Prod Eng 13:399–407. https://doi.org/10.1007/s11740-019-00886-3
Kumar SP, Elangovan S (2020) Optimization in single point incremental forming of Inconel 718 through response surface methodology. Trans Can Soc Mech Eng 44:148–160. https://doi.org/10.1139/tcsme-2019-0003
Zhou YJ, Lan FC, Huang XH, Chen JQ (2011) Multi-objective optimization of geometry of clinching tools for steel-aluminum blank sheets. Mater Sci Technol 19:86–93. https://doi.org/10.11951/j.issn.1005-0299.20110616
Kramer O (2017) Genetic algorithm essentials. Springer, Cham
Zhou G, Ma ZD, Li GY, Cheng AG, Duan LB, Zhao WZ (2016) Design optimization of a novel NPR crash box based on multi-objective genetic algorithm. Struct Multidisc Optim 54:673–684. https://doi.org/10.1007/s00158-016-1452-z
Funding
This work is supported by the National Natural Science Foundation of China (No. 52075299), Natural Science Foundation of Shandong Province (No. ZR2020ME149), and the Fundamental Research Funds of Shandong University (2018JC042).
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Haoyu Yuan: Writing–original draft preparation, investigation. Changdong Pan: Methodology, formal analysis. Libin Song: Resources, writing–review. Guoqun Zhao: Supervision. Chao Zheng: Conceptualization, writing–review and editing.
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Yuan, H., Pan, C., Song, L. et al. Modeling and optimization of laser shock hole-clinching using response surface methodology and genetic algorithm. Int J Adv Manuf Technol 122, 2391–2406 (2022). https://doi.org/10.1007/s00170-022-10056-y
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DOI: https://doi.org/10.1007/s00170-022-10056-y