The use of grey-based Taguchi methods to determine submerged arc welding process parameters in hardfacing
Introduction
Hardfacing involves the application of a deposition on the surface of a metallic workpiece by employing a welding method such as submerged arc welding (SAW) and has found widespread application in the steel industry, mining and in the petroleum industry [1]. The process of hardfacing should be aimed at achieving a strong bond between the deposit and the base metal with a high deposition rate. Therefore, it is very important for the proper selection of SAW process parameters to improve weld qualities in hardfacing [2], [3]. In this paper, the use of the grey-based Taguchi method to optimize the SAW process in hardfacing with considerations of multiple weld qualities such as deposition rate, dilution, and hardness is reported.
The Taguchi method [4], [5] is a systematic application of design and analysis of experiments for the purpose of designing and improving product quality. In recent years, the Taguchi method has become a powerful tool for improving productivity during research and development so that high quality products can be produced quickly and at low cost. However, the original Taguchi method was designed to optimize a single performance characteristic. Furthermore, optimization of multiple performance characteristics is much more complicated than optimization of a single performance characteristic [6], [7]. In this paper, the grey relational analysis [8] is used to investigate multiple performance characteristics in the Taguchi method for the optimization of SAW process in hardfacing.
The grey system theory proposed by Deng [9] in 1982 has been proven to be useful for dealing with poor, incomplete, and uncertain information. The grey relational analysis based on the grey system theory can be used to solve complicated inter-relationships among multiple performance characteristics effectively [10]. Through the grey relational analysis, a grey relational grade is obtained to evaluate the multiple performance characteristics. As a result, optimization of the complicated multiple performance characteristics can be converted into optimization of a single grey relational grade. It is shown by this study that the use of the Taguchi method with the grey relational analysis can greatly simplify the optimization procedure for determining the optimal welding parameters with the multiple performance characteristics in the SAW process.
In the following, an overview of the optimization of the multiple performance characteristics by the grey-based Taguchi method is given first. Then, the selection of SAW process parameters and the evaluation of SAW weld qualities are discussed. Optimization of the SAW process in hardfacing based on the grey-based Taguchi method is described in detail. Finally, the paper concludes with a summary of this study.
Section snippets
Grey-based Taguchi methods for optimization of process parameters
Optimization of process parameters is the key step in the Taguchi method in achieving high quality without increasing the cost. This is because optimization of process parameters can improve performance characteristics and the optimal process parameters obtained from the Taguchi method are insensitive to the variation of environmental conditions and other noise factors. Basically, classical process parameter design [11] is complex and not easy to use. Especially, a large number of experiments
The SAW process in hardfacing
SAW is an effective hardfacing method for welding on worn metal surfaces with repeated depositions. The metal surface that is worn away can be restored to its original state because of a strong bond between the deposit and the base metal. In the SAW process, the arc is generated between a continuously fed electrode and the base metal is hidden under a granular flux blanket. The heat of the arc is used to melt the surface of the base metal and the end of the electrode, where protection for the
Determination of welding process parameters
In this section, the use of the grey-based Taguchi method to determine the welding process parameters is reported step-by-step. Optimal welding process parameters with considerations of the multiple performance characteristics are obtained and verified.
Conclusion
The use of the grey-based Taguchi method to determine the SAW process parameters with consideration of multiple performance characteristics has been reported in this paper. A grey relational analysis of the S/N ratios can convert the optimization of the multiple performance characteristics into the optimization of a single performance characteristic called the grey relational grade. As a result, the optimization of the complicated multiple performance characteristics can be greatly simplified
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