• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 1997년도 특별강연 및 추계학술발표 개요집
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• pp.229-233
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• 1997

The demand to increase productivity and quality, the shortage of skilled labour and the strict health and safety requirements have led to the development of the automated welding process to deal with many of the present problems of welded fabrication. To make effective use of the automated arc welding process, it is imperative that a mathematical model, which can be programmed easily and fed to the robot, should be developed. The objectives of the paper are to develop the mathematical equations (linear and curvilinear) for study of the relationship between process variables and bead geometry by employing a standard statistical package program, SAS and to choose the best model for automation of the $CO_2$ gas arc welding process. Mathematical models developed from experimental results can be employed to control the process variables in order to achieve the desired bead geometry based on weld quality criteria. Also these equations may prove useful and applicable for automatic control system and expert systems.

• Journal of Welding and Joining
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• 제24권5호
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• pp.37-42
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• 2006

The robotic arc welding is widely employed in the fabrication industry fer increasing productivity and enhancing product quality by its high processing speed, accuracy and repeatability. 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. In this paper, the possibilities of the Infrared camera in sensing and control of the bead geometry in the automated welding process are presented. Both bead width and thermal images from infrared thermography are effected by process parameters. Bead width and isotherm radii can be expressed in terms of process parameters(welding current and welding speed) using mathematical equations obtained by empirical analysis using infrared camera. A linear relationship exists between the isothermal radii producted during the welding process and bead width.

• Journal of Welding and Joining
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• 제28권4호
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• pp.73-80
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• 2010

In this work, the effect of welding variables on weldability of gas tungsten arc(GTA) welding was investigated with experimental analysis for a commercial pure(CP) titanium (Grade.1). The GTA welding tests on sheet samples with 0.5mm in thick were carried out at different process variables such as arc length, welding speed and electrode shape. In order to search an optimum arc length with full penetration, bead- on-plate welding before butt-welding were performed with different arc length conditions. From the bead- on-plate welding results, the optimum condition considering arc stability and electrode loss was obtained in the arc length of 0.8mm. Butt-welding tests based on the arc length of 0.8mm were carried out to achieve the optimum conditions of welding speed and electrode shape. Optimum conditions of welding speed and electrode shape were suggested as 10 mm/s and truncated electrode shape, respectively. It was successfully validated by the microstructural observation, tensile tests, micro-hardness tests and formability tests.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.608-611
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• 2002

In GMAW(Gas Metal Arc Welding) process, bead geometry (penetration, bead width and height) is a criterion to estimate welding quality. Bead geometry is affected by welding current, arc voltage and travel speed, shielding gas, CTWB (contact- tip to workpiece distance) and so on. In this paper, welding process variables were selected as welding current, arc voltage and travel speed. And bead geometry was reasoned from the chosen welding process variables using negro-fuzzy algorithm. Neural networks was applied to design FL(fuzzy logic). The parameters of input membership functions and those of consequence functions in FL were tuned through the method of learning by backpropagation algorithm. Bead geometry could be reasoned from welding current, arc voltage, travel speed on FL using the results learned by neural networks.

• Journal of Welding and Joining
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• 제18권3호
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• pp.114-121
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• 2000

Since resistance spot welding has become one of the most popular sheet metal fabrication processes, a strong emphasis is being put on the quality of the welds. Throughout the years many quality estimation systems have been developed by many researchers to ensure weld quality. In this study, the process variables, which were monitored in the primary circuit of the welding machine, are used to estimate the weld quality with Hopfield neural network. The primary dynamic resistance is vectorized and stored as five patterns in the network. As the welding is done, the dynamic resistance patterns are recognized and the quality is estimated with the proposed method. Due to the primary process variables, it is possible to utilize this algorithms as an in-process real time quality monitoring system.

• Journal of Welding and Joining
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• 제32권2호
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• pp.22-28
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• 2014

To enhance productivity and provide high quality production material in a GMA welding process, weld quality, productivity and cost reduction affects the number of process variables. In addition, a reliable welding process and conditions must be implemented to reduce weld structure failure. In various industries the welding process mathematical model is not fully formulated for the process parameter and on the welding conditions, therefore only partial variables can be predicted. The research investigates the interaction between the welding parameters (welding speed, distance between electrodes, and flow rate of shielding gas) and bead geometry for predicting the weld bead geometry (bead width, bead height). Taguchi techniques are applied to bead shape to develope curve equation for predicting the optimized process parameters and quality characteristics by analyzing the S/N ratio. The experimental results and measured error is within the range of 10% presenting satisfactory accuracy. The curve equation was developed in such a way that you can predict the bead geometry of constructed machinery that can be used for making tandem welding process.

• 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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• 제15권6호
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• pp.66-77
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• 1997

In the present work, Taguchi method for electron beam welding(EBW) process in AISI 4130 steel plate has been adopted for investigating the contribution of effect of welding variables. $A L_8(2^7)$ orthogonal array is adopted to obtain the effect of adjustment parameters. The adjustment parameters consist of accelerating voltage, beam current, travel speed and focus currrent. And the quality features selected for the EBW process are bead width of weldment, reinforcement, penetration depth, undercut and area of weld metal. Variance analysis is performed in order to check the effect of adjustment parameters on EBW. The mechanical properties of electron beam welded joints for each heat treatment conditions are investigated in comparison with those of base metal, especially from the view point of tensile and impact properties.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2004년도 춘계공동학술대회 논문집
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• pp.487-493
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• 2004

This paper consider a six sigma project for improving the TIP life time in a spot welding process. The project follows a disciplined process of five phases: define, measure, analyze, improve, and control. A process map is used to identify process input and output variables. Nine key process input variables are selected by using C&E matrix and FMEA, and finally four vital few input variables are selected from analyze phase. The optimum process conditions of the four vital few input variables are jointly obtained by maximizing TIP life time using DOE.

• Journal of Welding and Joining
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• 제17권4호
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• pp.39-45
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• 1999

The procedure of robotic Gas metal Arc (GMA) welding in order to achieve the optimized bead geometry needs the selection of suitable process parameters such as arc current, welding voltage, welding speed. It is required the relationships between process parameters and bead geometry. The objective of this paper is to develop the algorithm that enables the determination of process parameters from the optimized bead geometry for robotic GMA welding. It depends on the inversion of empirical equations derived from multiple regression analysis of the relationships between the process parameters and the bead dimensions using the least square method. The method not only directly determines those parameters which will give the desired set of bead geometry, but also avoids the need to iterate with a succession of guesses employed Finite Element Method(FEM). These results suggest that process parameter from experimental equation for robotic GMA welding may be employed to monitor and control the bead geometry in real time.