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

Abstract

In this paper, an additional filler wire with opposite polarity was inserted in tandem flux cored arc welding process to increase the welding speed and deposition rate. In this hybrid welding, the optimisation of welding parameters is required to improve the bead geometry which directly indicates the welding quality. However, the correlation between the parameters and the bead geometry is hard to identify, so the process parameters are usually selected intuitively by the experienced engineers. Therefore, welding process modelling is constructed with the Gaussian process regression model, and parameter optimisation is performed with sequential quadratic programming optimisation algorithm. The proposed modelling optimisation process is verified by performing the welding experiment using the parameters that are optimised by the proposed process.

Keywords:

• Tandem flux cored arc welding
• hot-wire
• hybrid tandem metal active gas welding
• Gaussian process regression
• parameter optimisation
• fillet welding
• machine learning

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Dae Young Lee http://orcid.org/0000-0002-6083-1805

Additional information

Funding

This work was supported by Korea Evaluation Institute of Industrial Technology (KEIT) grant funded by the Korea government (MOTIE) (No. 10062648).