Optimisation of spot-welding process using Taguchi based Cuckoo search algorithm
DOI:
https://doi.org/10.31181/dmame0318062022cKeywords:
Spot welding, Cuckoo Search method, Taguchi method, optimization, Peak loadAbstract
The present work evaluated the efficiency of a Taguchi-based Cuckoo Search (CS) algorithm for optimizing the spot-welding process. The L9 orthogonal array of the Taguchi method is used for the conduction of required experiments. During the study input parameters are welding current (kA), hold time (cycles), welding time (cycles), and electrode pressure (kPa) while Peak Load, kN has been considered as an output parameter. The required objective function is developed through regression model formulation. Initially, CS operating parameters such as maximum number of iterations, number of nests, and probability to discover a cuckoo egg by the host bird is optimized through the Taguchi method and are found as 40, 20, and 0.5 respectively. That optimized CS further optimizes the spot-welding process. The maximum peak load of 34.5 kN is obtained if the welding current is 30.7 kA, welding time is 32 cycles, hold time is 20 cycles, and electrode pressure is 480 kPa respectively. Experimental validation yields a very low % error of 1.93% during optimization with an optimized CS method and the error is substantially high if optimization is conducted using a non-optimized CS method.
Downloads
References
Bozkurt, F., & Çakır, F.H. (2021). An experimental design of spot welding of Ti6Al4V sheets and numerical modeling approach. Welding in the World, 65, 885–898.
Cao, X., Li, Z., Zhou, X., Luo, Z., & Duan, J., (2021). Modeling and optimization of resistance spot welded aluminum to Al-Si coated boron steel using response surface methodology and genetic algorithm. Measurement, 171, 108766.
Chaki, S., Ghosal, S., & Bathe, R. N., (2012). Kerf quality prediction and optimisation for pulsed Nd: YAG laser cutting of aluminium alloy sheets using GA-ANN hybrid model. International Journal of Mechatronics and Manufacturing Systems, 5, 263-279.
Choudhary, A., Kumar, M., Gupta, M. K., Unune, D. K., & Mia, M. (2020). Mathematical modeling and intelligent optimization of submerged arc welding process parameters using hybrid PSO-GA evolutionary algorithms. Neural Computing and Applications, 32, 5761-5774.
Dhawale, P. A., & Ronge, B. P. (2019). Parametric optimization of resistance spot welding for multi spot welded lap shear specimen to predict weld strength. Materials Today: Proceedings, 19, 700-707.
Ebrahimpour, A., Mostafapour, A., & Nakhaei, M. R. (2021). Application of response surface methodology for weld strength prediction in FSSWed TRIP steel joints. Welding in the World, 65, 183-198.
Fatmahardi, I., Mustapha, M., Ahmad, A., Derman, M. N., Lenggo Ginta, T., & Taufiqurrahman, I. (2021). An Exploratory Study on Resistance Spot Welding of Titanium Alloy Ti-6Al-4V. Materials, 14(9), 2336.
Jiang, P., Liu, F., Wang, J., & Song, Y. (2016). Cuckoo search-designated fractal interpolation functions with winner combination for estimating missing values in time series. Applied Mathematical Modelling, 40(23-24), 9692-9718.
Kumar, R., Chohan, J. S., Goyal, R., & Chauhan, P. (2021). Impact of process parameters of resistance spot welding on mechanical properties and micro hardness of stainless steel 304 weldments. International Journal of Structural Integrity, 12(3), 366-377.
Mohanty, C. P., Mahapatra, S. S., & Singh, M. R. (2017). An intelligent approach to optimize the EDM process parameters using utility concept and QPSO algorithm. Engineering Science and Technology, an international journal, 20(2), 552-562.
Neystani, R., Beidokhti, B., & Amelzadeh, M. (2019). Fabrication of dissimilar Fe-Cu-C powder metallurgy compact/steel joint using the optimized resistance spot welding. Journal of Manufacturing Processes, 43, 200-206.
Pattanaik, A. K., Panda, S. N., Pal, K., & Mishra, D. (2018). A comparative investigation to process parameter optimization for spot welding using Taguchi based grey relational analysis and metaheuristics. Materials Today: Proceedings, 5(5), 11408-11414.
Al-Sabur, R. (2021). Tensile strength prediction of aluminium alloys welded by FSW using response surface methodology–Comparative review. Materials Today: Proceedings, 45, 4504-4510.
Saravanan, M., Thiyagarajan, C., & Somasundaram, S. (2020). Parametric optimization of wirecut-electrical discharge machining through cuckoo search algorithm. Materials Today: Proceedings, 22, 681-687.
Shastri, R. K., & Mohanty, C. P. (2021). Sustainable electrical discharge machining of Nimonic C263 superalloy. Arabian Journal for Science and Engineering, 46, 7273-7293.
Swathypriyadharsini, P., & Premalatha, K. (2021). Hybrid cuckoo search with clonal selection for triclustering gene expression data of breast cancer. IETE Journal of Research
Tyagi, A., Kumar, G., Kumar, M., & Wahid, M. A. (2022). Analysis the effect of process parameters on robot spot welding of JSC 590RN mild steel using Taguchi based GRA. Materials Today: Proceedings, 51, 1006-1011.
Gu, W., Li, Z., Dai, M., & Yuan, M. (2021). An energy-efficient multi-objective permutation flow shop scheduling problem using an improved hybrid cuckoo search algorithm. Advances in Mechanical Engineering, 13(6), 16878140211023603.
Xiao, L., Shao, W., Yu, M., Ma, J., & Jin, C. (2017). Research and application of a hybrid wavelet neural network model with the improved cuckoo search algorithm for electrical power system forecasting. Applied energy, 198, 203-222.
Yang, X. S., & Deb, S. (2010). Engineering optimisation by cuckoo search. International Journal of Mathematical Modelling and Numerical Optimisation, 1(4), 330-343.
Zhao, D., Wang, Y., Wang, X., Wang, X., Chen, F., & Liang, D. (2014). Process analysis and optimization for failure energy of spot welded titanium alloy. Materials & Design, 60, 479-489.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 Decision Making: Applications in Management and Engineering
This work is licensed under a Creative Commons Attribution 4.0 International License.
