تجزیه و تحلیل حساسیت پارامترهای پروسه در فرآیندهای جوشکاری GMA با ​​استفاده از روش طراحی فاکتوریل

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 and shape to accomplish the desired mechanical properties of the weldment should be developed. This paper focuses on the development of mathematical models for the selection of process parameters and the prediction of bead geometry (bead width, bead height and penetration) in robotic GMA (Gas Metal Arc) welding. Factorial design can be employed as a guide for optimization of process parameters. Three factors were incorporated into the factorial model: arc current, welding voltage and welding speed. A sensitivity analysis has been conducted and compared 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.

Recently automated and/or robotic welding systems have received a great deal of attention because they are highly suitable not only to increased production rate and quality, but also to decreased cost and time to manufacture for a given product. To get the desired quality welds, it is essential to have complete control over the relevant process parameters in order to obtain the required bead geometry and which is also based on weldability. However, mathematical models need to be developed to make effective use of automated and/or robotic arc welding. Previous work on the relationships between process parameters and bead geometry in the arc welding process can be grouped into two distinct areas; empirical methods based on studies of actual welding situations [1], [2] and [3] and theoretical studies based on heat flow theory [4], [5] and [6]. An early attempt at The Welding Institute [2] succeeded in selecting a statistical approach to evaluate the relationships between submerged-arc welding variables and bead geometry. Chandel [7] first applied this technique to a GMA welding process and investigated relationships between process parameters and bead geometry of bead-on-plate welds deposited by a GMA welding process. These results showed that arc current has the greatest influence on bead geometry, and that mathematical models derived from experimental results can be employed to predict bead geometry. Doumanidis et al. [8] have attempted to derive simple dynamic models in their attempt to control bead width, penetration, heat affected zone and cooling rate at the centerline of the weld. Despite the large numbers of attempts to analyze arc welding processes, mathematical models between input and output parameters in the arc welding process are still lacking. 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 by a known amount and evaluating the new results. Chuang and Hou [9] developed a sensitivity formulation for a planar frame parameter joint and support locations as design parameters. Also, Son and Kwak [10] 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, Lee and Albright [11] 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 process parameters can be determined using sensitivity analysis. However, they insisted that it is not accurate as it is simplistic and does not take into account of all the relevant parameters involved in the welding process. Since then, various models have been proposed to improve arc welding models for the prediction of process parameters. Although significant progress has been made, there is still the lack of a mathematical model that can predict bead geometry over a wide range of welding conditions. In this paper, a methodology for understanding relationships between process parameters and bead geometry, and development of mathematical models for the GMA welding process is presented. The objective of the first part of this study is to find the optimal bead geometry in the GMA welding process. A statistical three-level factorial analysis for optimization of process parameters in bead geometry was performed, and mathematical models using a commercial statistical package SAS were developed. A sensitivity analysis based on the developed empirical equations has been carried out. Finally the sensitivity results have been compared to 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. The optimal bead geometry is based on bead width, bead height and penetration. The factorial design has been adopted to solve the optimal bead geometry. Experimental results have shown that process parameters such as welding speed, arc current and welding voltage influence the bead width, bead height and penetration in GMA welding processes. Mathematical models developed from the experimental data can be employed to study relationships between process parameters and bead geometry and to predict the bead dimensions within 0–25% accuracy. 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 the potential for more stringent sensitivity analysis and may be used for optimal parameter estimation for other mathematical models.