537
Views
13
CrossRef citations to date
0
Altmetric
Research Articles

Optimisation of hybrid tandem metal active gas welding using Gaussian process regression

ORCID Icon, , & ORCID Icon
Pages 208-217 | Received 29 Jul 2019, Accepted 05 Sep 2019, Published online: 18 Sep 2019

References

  • Yokota Y, Shimizu H, Nagaoka S, et al. Development and application of the 3-electrode mag high-speed horizontal fillet welding process. Weld World. 2012;56(12):43–47. doi: 10.1007/BF03321144
  • Srivastava S, Garg R. Process parameter optimization of gas metal arc welding on is: 2062 mild steel using response surface methodology. J Manuf Process. 2017;25:296–305. doi: 10.1016/j.jmapro.2016.12.016
  • Singh RP, Garg R, Shukla DK. Mathematical modeling of effect of polarity on weld bead geometry in submerged arc welding. J Manuf Process. 2016;21:14–22. doi: 10.1016/j.jmapro.2015.11.003
  • Lostado Lorza R, Escribano Garcá R, Martńez Calvo M, et al. Improvement in the design of welded joints of en 235jr low carbon steel by multiple response surface methodology. Metals. 2016;6(9):205. doi: 10.3390/met6090205
  • Sen M, Mukherjee M, Pal T. Evaluation of correlations between dp-gmaw process parameters and bead geometry. Weld J. 2015;94(8):265s–279s.
  • Singh A, Datta S, Mahapatra SS, et al. Optimization of bead geometry of submerged arc weld using fuzzy based desirability function approach. J Intel Manuf. 2013;24(1):35–44. doi: 10.1007/s10845-011-0535-3
  • Nagaraju S, Vasantharaja P, Chandrasekhar N, et al. Optimization of welding process parameters for 9Cr–1Mo steel using RSM and GA. Mater Manuf Process. 2016;31(3):319–327. doi: 10.1080/10426914.2015.1025974
  • Shahi A, Pandey S. Welding current prediction in GMAW and UGMAW processes using response surface methodology. Sci Tech Weld Join. 2006;11(3):341–346. doi: 10.1179/174329306X113253
  • Xu W, Lin S, Fan C, et al. Prediction and optimization of weld bead geometry in oscillating arc narrow gap all-position GMA welding. Int J Adv Manuf Tech. 2015;79(1–4):183–196. doi: 10.1007/s00170-015-6818-7
  • Sterling D, Sterling T, Zhang Y, et al. Welding parameter optimization based on Gaussian process regression Bayesian optimization algorithm. In: 2015 IEEE International Conference on Automation Science and Engineering (CASE); IEEE; 2015. p. 1490–1496.
  • Chen T, Morris J, Martin E. Gaussian process regression for multivariate spectroscopic calibration. Chemometr Intell Lab Sys. 2007;87(1):59–71. doi: 10.1016/j.chemolab.2006.09.004
  • Likar B, Kocijan J. Predictive control of a gas–liquid separation plant based on a Gaussian process model. Comput Chem Eng. 2007;31(3):142–152. doi: 10.1016/j.compchemeng.2006.05.011
  • Yuan J, Wang K, Yu T, et al. Reliable multi-objective optimization of high-speed WEDM process based on Gaussian process regression. Int J Mach Tools Manuf. 2008;48(1):47–60. doi: 10.1016/j.ijmachtools.2007.07.011
  • Vasudevan S, Ramos F, Nettleton E, et al. Gaussian process modeling of large-scale terrain. J Field Robot. 2009;26(10):812–840. doi: 10.1002/rob.20309
  • Schneider M, Ertel W. Robot learning by demonstration with local Gaussian process regression. In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems; IEEE; 2010. p. 255–260.
  • Yang K, Keat Gan S, Sukkarieh S. A Gaussian process-based RRT planner for the exploration of an unknown and cluttered environment with a UAV. Adv Robot. 2013;27(6):431–443. doi: 10.1080/01691864.2013.756386
  • Frank B, Stachniss C, Abdo N, et al. Using Gaussian process regression for efficient motion planning in environments with deformable objects. In: Workshops at the 25th AAAI Conference on Artificial Intelligence; 2011.
  • Jadaliha M, Xu Y, Choi J, et al. Gaussian process regression for sensor networks under localization uncertainty. IEEE Trans Signal Proc. 2013;61(2):223–237. doi: 10.1109/TSP.2012.2223695
  • Dong H, Cong M, Liu Y, et al. Predicting characteristic performance for arc welding process. In: 2016 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER); IEEE; 2016. p. 7–12.
  • Verma S, Gupta M, Misra JP. Performance evaluation of friction stir welding using machine learning approaches. Meth X. 2018;5:1048–1058.
  • Sterling T, Chen H. Robotic welding parameter optimization based on weld quality evaluation. In: 2016 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER); IEEE; 2016. p. 216–221.
  • Huff SA. Tig welding skill extraction using a machine learning algorithm [Master's thesis]. Texas State University; 2017.
  • Tapia G, Elwany A, Sang H. Prediction of porosity in metal-based additive manufacturing using spatial gaussian process models. Additive Manuf. 2016;12:282–290. doi: 10.1016/j.addma.2016.05.009
  • Kim DH, Kim TJ, Wang X, et al. Smart machining process using machine learning: A review and perspective on machining industry. Inter J Precision Engin Manuf Green Tech. 2018;5(4):555–568. doi: 10.1007/s40684-018-0057-y
  • Zhou Q, Wang Y, Choi SK, et al. Robust optimization for reducing welding-induced angular distortion in fiber laser keyhole welding under process parameter uncertainty. Appl Thermal Engin. 2018;129:893–906. doi: 10.1016/j.applthermaleng.2017.10.081
  • Yokota Y, Shimizu H, Nagaoka S, et al. Development and application of the 3-electrode mag high-speed horizontal fillet welding process. Weld World. 2012;56(1–2):43–47. doi: 10.1007/BF03321144
  • Arita H, Morimoto T, Nagaoka S, et al. Development of advanced 3-electrode mag high-speed horizontal fillet welding process. Weld World. 2009;53(5–6):35–43. doi: 10.1007/BF03266713
  • Rasmussen CE, Williams CKI. Gaussian processes for machine learning. Cambridge; 2006.
  • Simpson TW, Mauery TM, Korte JJ, et al. Kriging models for global approximation in simulation-based multidisciplinary design optimization. AIAA J. 2001;39(12):2233–2241. doi: 10.2514/2.1234
  • Neal RM. Bayesian learning for neural networks. Toronto (Ontario): Springer Science & Business Media; 2012.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.