• Proceedings of the KWS Conference
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• 2002.05a
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• pp.68-70
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• 2002

A CCD camera with a laser strip was applied to realize the automation of welding process in GMAW. The Hough transformation was used to extract the laser stripe and to obtain specific weld points. In this study, a neural network based on the generalized delta rule algorithm was adapted for the process control of GMA, such as welding speed, arc voltage and wire feeding speed.

• Journal of Welding and Joining
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• v.35 no.1
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• pp.16-25
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• 2017

Gas Metal Arc Welding is a widely used process in Industry due to its high productivity and potential to automation. The present study investigates the effects of the welding speed, arc voltage, welding current and shielding gas on the bead geometry for a low-carbon steel. The Response Surface Methodology (RSM) is used to choose an experimental design and perform test runs accordingly in order to produce mathematical models predicting the geometry, the hardness and the heat input of the bead as functions of the welding parameters. The direct and interaction effects of the four welding parameters are represented graphically and allow to determine an optimum set of welding parameters.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.606-611
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• 2002

Welding using lasers can be mass-produced in high speed. In the laser welding, performing real-time monitoring system of the welding quality is very important in enhancing the efficiency of welding. In this study, the plasma and molten metal which are generated during laser welding were measured using the UV sensor and IR sensors. The results of laser welding were classified into five categories such as optimal heat input, little low heat input, low heat input, partial joining due to gap mismatch, and nozzle deviation. Also, a system was formulated which uses the measured signals with a fuzzy pattern recognition method which is used to perform real-time evaluation of the welding quality and the defects which can occur in laser welding.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.516-519
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• 1996

Sub-assembly in ship manufacturing is a sequence of filet joint welding of stiffeners on metal panels and the process is different depending on companies. In this paper, we introduce a new intelligent robotic system of the sub-assembly process in Samsung Heavy Industry, where one shift of 22m * 9m workspace includes one to ten panels and each panel includes up to 10 stiffeners. The inherent problems such as several hundreds of different panels, unstructured task environment and the large scale do not allow a fixed automation, but needs highly intelligent versatile automation. The robotic system is composed of four 14DOF macro-mini robots and a task recognition system. Application of this system has verified the task specification such as low temperature environment(-10.deg. C) and productivity is satisfied successfully.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.3
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• pp.243-251
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• 2015

In order to develop an automatic system for welding thin steel plates with curvature such as the corrugated membranes of an LNG storage tank, a rotating mechanism should be firstly designed for the torch to easily follow the weld seam with a constant distance and angle. In this study, a torch rotating mechanism consisting of three circular links, two square-type links and a torch link was proposed for automation of the welding process. A weld-seam tracking system with two axis slides and the proposed rotating mechanism was successfully simulated with a dynamic simulation software. A prototype tracking system was manufactured and a tracking test with the system was then carried out. The test results with tracking system showed that the rotating mechanism could be implemented and it was feasible to be used in automatic tracking of weld seam with curvature.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1845-1848
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• 2005

The automatic $CO_2$ welding is a manufacturing process to produce high quality joints for metal and it could provide a capability of full automation to enhance productivity. Despite the widespread use in the various manufacturing industries, the full automation of the robotic $CO_2$ welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this research, an attempt has been made to develop an intelligent algorithm to predict the weld geometry (top-bead width, top-bead height, back-bead width and back-bead height) as a function of key process parameters in the robotic $CO_2$welding. 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.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.4
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• pp.89-95
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• 1997

Welding technique is widely applied to general industry such as pressure vessel for chemical plant, pipe system, heavy industry, and automobile. There are some points which must be considered when robot system is used in welding automation process for productivity improvement. Welding quality is governed by heat input, and this quantity can be different according to shape, property, and thick of material . For desired heat input , weld input parameters such as welding voltage, current, and welding velocity must be determined with those consideration. Until now these parameters have been determined mainly by experience of operator. In this study, the size of welding zone was predicted by fuzzy rules were constructed from the relation between welding variables and weld pool size. Inverse model method which welding control input for welder is determined with optimum voltage and current by fuzzy controller is validatied by computer simulation.

• Journal of Welding and Joining
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• v.29 no.6
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• pp.82-87
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• 2011

In this study, we conducted laser welding by using remote scanner that is 5J32 aluminum alloy to observe the mechanical properties and optimize welding process parameters. As the control factors, laser incident angle, laser power and welding speed were set and as the result of weldablility, tensile shear tests were performed. ANOVA (Analysis of Variation) was also carried out to identify the influence of process variables on tensile shear strength. Strength estimation models were suggested using regression alnalysis and 2nd order polynomial model had the best estimation performance. In addition optimal welding condition was determined in terms with wedalility and productivity using objective function and fitness function. Final optimized welding condition was laser power was 4 kW, and welding speed was 4.6 m/min.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.342-348
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• 2002

The welding technology for production of power plant facility as for other industries has been progressing forward automation and mechanization for cost reduction and shortening of cycle time. The welding for boiler tube is automated or mechanized as the parts and subassemblies of tubes are conveyed automatically in the shop. The temperature of boiler stearn is being progressively increased for higher plant efficiency. The welding of nuclear component is characterized by heavy thickness and narrow gap Submerged Arc Welding. Narrow gap Gas Metal Arc Welding and Electron Beam Welding is applied to turbine diaphragm. To improve the resistance of solid particle erosion of turbine blade and nozzle partition, HVOF spray technology and boriding process has been applied.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.124-132
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• 2001

Autonomous of welding process in shipyard is ultimately necessary., since welding site is spatially enclosed by floors and girders, and therefore welding operators are exposed to hostile working conditions. To solve this problem, a welding robot that can navigate autonomously within the enclosure needs to be developed. To achieve the welding ra나, the robotic welding systems needs a sensor system for the recognition of the working environments and the weld seam tracking, and a specially designed environment recognition strategy. In this paper, a three-dimensional laser vision system is developed based on the optical triangulation technology in order to provide robots with work environmental map. At the same time a strategy for environment recognition for welding mobile robot is proposed in order to recognize the work environment efficiently. The design of the sensor system, the algorithm for sensing the structured environment, and the recognition strategy and tactics for sensing the work environment are described and dis-cussed in detail.