• International Journal of Korean Welding Society
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• 제3권1호
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• pp.8-16
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• 2003

A major concern in Gas Metal Arc (GMA) welding process is the determination of welding process variables such as wire diameter, gas flow rate, welding speed, arc current and welding voltage and their effects on the desired weld bead dimensions and shape. To successfully accomplish this objective, 81 welded samples from mild steel AS 1204 flats adopting the bead-on-plate technique were employed in the experiment. The experimental results were used to develop a mathematical model to predict the magnitude of bead geometry as follows; weld bead width, weld bead height, weld bead penetration depth, weld penetration shape factor, weld reinforcement shape factor, weld bead total area, weld bead penetration area, weld bead reinforcement area, weld bead dilution, length of weld bead penetration boundary and length of weld bead reinforcement boundary, and to establish the relationships between weld process parameters and bead geomery. Multiple regression analysis was employed for investigating and modeling the GMA process and significance test techniques were applied for the interpretation of the experimental data.

• Journal of Welding and Joining
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• 제32권3호
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• pp.1-10
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• 2014

The efficient application of any welding process depends on the understanding of associated process parameters influence on the weld quality. The weld quality includes the weld bead dimensions, temperature distribution, metallurgical phases and the mechanical properties. A detailed review on the experimental and numerical approaches to understand the parametric influence of a single wire submerged arc welding (SAW) and multi-wire SAW processes on the final weld quality is reported in two parts. The first part deals with the experimental approaches which explain the parametric influence on the weld bead dimensions, metallurgical phases and the mechanical properties of the SAW weldment. Furthermore, the studies related to statistical modeling of the present welding process are also discussed. The second part deals with the numerical approaches which focus on the conduction based, and heat transfer and fluid flow analysis based studies in the present welding process. The present paper is the first part.

• Journal of Welding and Joining
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• 제32권4호
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• pp.1-9
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• 2014

A quantitative understanding on the effect of the welding conditions on weld joint dimensions and weld thermal cycle is difficult through experimental studies alone. The experimental realization of temperature distribution in the weld pool is proved to be extremely difficult due to the small size of welds, high peak temperature and steep temperature gradients in weld pool. This review deals with the heat transfer and fluid flow analysis to understand the parametric influence of a single wire submerged arc welding (SAW) and multi-wire SAW processes on the weld bead dimensions, temperature and fluid flow distribution in the weldment.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2003년도 춘계학술발표대회 개요집
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• pp.81-83
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• 2003

The potential advantages of the hybrid welding process are improved weld penetration, enhanced gap tolerance, control of weld metal composition, and improved weld quality in comparison to laser or arc welding. Especially, the deep penetration of hybrid welding is very attractive in welding of thick plates. In this study, therefore, the influence of arc power in hybrid welding on detailed bead dimensions at different laser power levels was investigated.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 추계학술대회 논문집
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• pp.754-758
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• 2005

Optimization of process variables such as arc current, welding voltage and welding speed in terms of the weld characteristics desired is the key step in achieving high quality and improving performance characteristics without increasing the cost. Consequently, incorrect settings of those process variables give rise to deviations in the welding characteristics from the desired bead geometry. Therefore, trainee welders are referred to the tabulated information relating different metal types and thickness as to recommend the desired values of process variables. Basically, the bead geometry plays an important role in determining the mechanical properties of the weld. So that it is very important to select the process variables for obtaining optimal bead geometry. However, it is difficult for the traditional identification methods to provide an accurate model because the optimized welding process is non-linear and time-dependent. In this paper, the possibilities of the Infra-red sensor in sensing and control of the bead geometry in the automated welding process are presented. Infra-red sensor is a well-known method to deal with the problems with a high degree of fuzziness so that the sensor is employed to build the relationship between process variables and the quality characteristic the proposed above respectively. Based on several neural networks, the mathematical models are derived from extensive experiments with different welding parameters and complex geometrical features. The developed system enables to select the optimal welding parameters and control the desired weld dimensions during arc welding process.

• Journal of Welding and Joining
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• 제25권6호
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• pp.64-70
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• 2007

Recently, several models to control weld quality, productivity and weld properties in arc welding process have been developed and applied. Also, the applied model to make effective use of the robotic GMA(Gas Metal Arc) welding process should be given a high degree of confidence in predicting the bead dimensions to accomplish the desired mechanical properties of the weldment. In this study, a development of the on-line learning neural network models that investigate interrelationships between welding parameters and bead width as well as apply for the on-line quality control system for the robotic GMA welding process has been carried out. The developed models showed an excellent predicted results comparing with the predicted ability using off-line learning neural network. Also, the system will extend to other welding process and the rule-based expert system which can be incorporated with integration of an optimized system for the robotic welding system.

• Journal of Welding and Joining
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• 제32권1호
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• pp.28-33
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• 2014

In this paper, I-butt welding with 6mm thickness using Plasma-GMA welding was carried out. And weld characteristics of the Al-5083 aluminium alloy for Plasma-GMA hybrid welding was evaluated. The orthogonal experimental design was used to investigate the influence of plasma-MIG welding parameters such as plasma current, wire feeding rate, MIG-welding voltage and welding speed on the weld bead geometry and tensile strength using the ANOVA(Analysis of Variation). Then we conducted evaluation of contribution for process parameters. ANOVA results show that bead dimensions are affected by wire feeding speed, welding voltage and welding speed and tensile strength is mainly affected by welding speed and plasma arc current. Tensile strength was decreased by rise in plasma welding current because GMA welding current was decreased by plasma arc.

• Journal of Welding and Joining
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• 제12권1호
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• pp.59-72
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• 1994

This paper presents an on-line quality monitoring and control method to obtain a uniform weld quality in gas metal arc welding (GMAW) processes. The geometrical parameters of the weld pool such as the top bead width and the penetration depth plus half back width are utilized to assess the integrity of the weld quality. Since a good quality weld is characterized by a relatively high depth-to-width ratio in its dimensions, the second geometrical parameter is regulated to a desired one. The monitoring variables are the surface temperatures measured at various points on the top surface of the weldment which are strongly related to the formation of the weld pool The relationship between the measured temperatures and the weld pool size is implemented on the multilayer perceptrons which are powerful for realization of complex mapping characteristics through training by samples. For on-line quality monitoring and control, it is prerequisite to estimate the weld pool sizes in the region of transient states. For this purpose, the time history of the surface temperatures is used as the input to the neural estimator. The control purpose is to obtain a uniform weld quality. In this research, the weld pool size is directly regulated to a desired one. The proposed controller is composed of a neural pool size estimator, a neural feedforward controller and a conventional feedback controller. The pool size estimator predicts the weld pool size under growing. The feedforward controller compensates for the nonlinear characteristics of the welding process. A series of simulation studies shows that the proposed control method improves the overall system response in the presence of changes in torch travel speed during GMA welding and guarantees the uniform weld quality.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.301-302
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• 2006

In this paper, the possibilities of the Infra-red sensor in sensing and control of the bead geometry in the automated welding process are presented. Infra-red sensor is a well-known method to deal with the problems with a high degree of fuzziness so that the sensor is employed to build the relationship between process variables and the quality characteristic the proposed above respectively. Based on several neural networks, the mathematical models are derived from extensive experiments with different welding parameters and complex geometrical features. The developed system enables to select the optimal welding parameters and control the desired weld dimensions during arc welding process.