تجزیه و تحلیل حساسیت پارامترهای پروسه موثر بر کیفیت جوش در فرآیند جوشکاری رباتیک GMA

Generally, the quality of a weld joint is strongly influenced by process parameters during the welding process. In order to achieve high quality welds, mathematical models that can predict the bead geometry to accomplish the desired mechanical properties of the weldment should be developed. This paper focuses on development of mathematical models for the selection of process parameters and the prediction of bead geometry (bead width, bead height, and penetration) in robotic gas metal arc (GMA) welding. A sensitivity analysis has also been conducted and compared with the relative impact of three process parameters on bead geometry in order to verify the measurement errors on the values of the uncertainty in estimated parameters. The results obtained show that developed mathematical models can be applied to estimate the effectiveness of process parameters for a given bead geometry, and a change of process parameters affects the bead width and bead height more strongly than penetration relatively.

To get the desired quality welds, it is recently essential to have a complete control over the relevant process parameters to obtain the required bead geometry and which is based on capacity of weldment. However, mathematical model should be developed to make effective use of automated arc welding. Previous works on relationship between the process parameters and bead geometry in arc welding process can be grouped into two distinct areas: empirical methods based on studies of actual welding situations [1] and [2] and theoretical studies based on heat flow theory [3] and [4]. Despite the large number of attempts to analyse arc welding process, there is still the lack of a mathematical model that can predict bead geometry over a wide range of welding conditions. Sensitivity analysis, a method to identify critical parameters and rank them by their order of importance, is paramount in model validation where attempts are made to compare the calculated output to the measured data. This type of analysis can study which parameters must be most accurately measured, thus determining the input parameters exerting the most influence upon model outputs. It differs considerably from the usual approach of perturbing a process parameter of a known amount and evaluating the new results. Chuang and Hou [5] developed a sensitivity formulation for a planar frame parameter joint and support locations as design parameters. Also, Son and Kwak [6] established a sensitivity formulation for eigenvalues, including repeated eigenvalues, with respect to the change of boundary conditions. The tangential design velocity component was employed to present the change of boundary conditions. Recently, Choi et al. [7] proposed sensitivity analysis for laser surface treatment by the differentiation of the analytic solution with respect to the laser beam radius and beam scanning velocity. It is evident that the qualitative and quantitative effectiveness of the process parameters can be determined using sensitivity analysis. In this paper, a methodology for understanding relationship between process parameters and bead geometry in gas metal arc (GMA) welding process is presented. The objective of this study is to find the optimal bead geometry in GMA welding process using mathematical models and to carry out a sensitivity analysis based on the developed empirical. Finally, the sensitivity results are compared and verified with the experimental results.

In this paper, the selection of the process parameters for GMA welding of AS 1204 steel plates with bead geometry has been reported. Mathematical models developed from the experimental data can be employed to study relationship between process parameters and bead geometry. Sensitivity analysis has been investigated to represent the effectiveness of the processing parameters on these empirical equations and showed that the change of process parameters affects the bead width and bead height more strongly than penetration relatively. The developed models should be put into perspective with the standard GMA welding power source that was employed to conduct the experimental work. Factorial analysis has a potential for more stringent sensitivity analysis and may be used for optimal parameter estimation for other mathematical models.