• Proceedings of the KWS Conference
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• 1999.10a
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• pp.142-145
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• 1999

The dynamic resistance monitoring is one of the important issues in that in-process and real time quality assurance of resistance spot weld is needed to increase the product reliability. Secondary dynamic resistance patterns, as a real manner, are hard to adapt those factors in real time and in-plant system. In the present study, a new dynamic resistance detecting method is presented as a practical manner of weld quality assurance at the primary circuit. By the correlation analysis, it is found that the primary dynamic resistance patterns are basically similar to those of the secondary. Various dynamic resistance indices are characterized with the primary curve. And quality of the weld, like the tensile shear strength, is estimated using adaptive neuro-fuzzy estimation system which is consisted of the Sugeno fuzzy algorithm. Through the fuzzy clustering and parameter optimization, real time weld quality assurance system with less efforts is proposed.

• Journal of Welding and Joining
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• v.20 no.6
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• pp.45-45
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• 2002

This study is a middle report on the development of intelligent spot welding monitoring technology applicable to the production line. An intelligent algorithm has been developed to predict the quality of welding in real time. We examined whether it is effective or not through the In-Line and the Off-Line tests. The purpose of the present study is to provide a reliable solution which can prevent welding defects in production site. In this study, the process variables, which were monitored in the primary circuit of the welding, are used to estimate the weld quality by Hidden Markov Model(HMM). The primary dynamic resistance patterns are recognized and the quality is estimated in probability method during the welding. We expect that the algorithm proposed in the present study is feasible to the applied in the production sites for the purpose of in-process real time quality monitoring of spot welding.

• Journal of Welding and Joining
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• v.20 no.6
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• pp.769-775
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• 2002

This study is a middle report on the development of intelligent spot welding monitoring technology applicable to the production line. An intelligent algorithm has been developed to predict the quality of welding in real time. We examined whether it is effective or not through the In-Line and the Off-Line tests. The purpose of the present study is to provide a reliable solution which can prevent welding defects in production site. In this study, the process variables, which were monitored in the primary circuit of the welding, are used to estimate the weld quality by Hidden Markov Model(HMM). The primary dynamic resistance patterns are recognized and the quality is estimated in probability method during the welding. We expect that the algorithm proposed in the present study is feasible to the applied in the production sites for the purpose of in-process real time quality monitoring of spot welding.

• Journal of Welding and Joining
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• v.30 no.3
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• pp.66-70
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• 2012

Welding is an essential process in the automotive industry. Most welding processes that are used for auto body is spot welding. And $CO_2$ arc welding is used in a small part. In production field, $CO_2$ arc welding process is decreased and spot welding process is increased due to welding quality is poor and defects are occurred in $CO_2$ arc welding process frequently. But $CO_2$ arc welding process should be used at robot interference parts and closed parts where spot welding couldn't. $CO_2$ welding is divided into lap welding and plug arc spot welding. In case of plug arc spot welding, burn through and under fill were caused in various welding environment such as different thickness combinations of base metal, teaching point, over the two steps welding and inconsistent voltage/current. It makes some problem like poor quality of welding area and decrease the productivity. In this study, we will evaluate the effect of teaching point through the weld pool behavior and bead geometry in the arc spot welding at the plut hole. Welding position is horizontal position. And galvanized steel sheet of 2.0mm thickness that has plug hole of 6mm diameter was used. Teaching point was changed by center, top, bottom, left and right of the plug hole. At each condition, the phenomenon of weld pool behavior was confirmed using a high-speed camera. As the result, we find the center of plug hole is the most optimal teaching point. In the other teaching point, under fill was occurred at the plug hole. This phenomenon is caused by gravity and surface tension. For performance of arc spot welding at the plug hole, the teaching condition should be controlled at a center of plug hole.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.370-373
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• 1988

Althouah there have been many attempts to control weld quality in resistance spot welding processes, design method for an on-line feedback controller based upon process dynamics has not been suggested. This is due to the fact that the resistance spot welding is a highly complicated process, whice involves the interaction of electrical, thermal, mechanical and metallurgical phenomena. In this paper, an optimal control method based on FDM model with shunt effect is presented, which can regulate the nugget size, at the same time minimizing the control heat input. Optimal PI gain of the controller were determined by numerical optimization. Simulation results show that, as a result of the proposed optimal control, the weld nugget can be made to approach a desired nugget size with less control heat input than that required for the conventional spot welding process in the face of the shunt effect.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.52-60
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• 2018

In the automobile industry, in order to increase the fuel efficiency and conform to the safety regulations, it is necessary to make the vehicles as light as possible. Therefore, it is crucial to manufacture dual phase steels, complex phases steels, MS steels, TRIP steels, and TWIP from high strength steels with a tensile strength of 700Mpa or more. In order to apply ultra-high tensile strength steel to the body, the welding process is essential. Resistance spot welding, which is advantageous in terms of its cost, is used in more than 80% of cases in body welding. It is generally accepted that ultra-high tensile strength steel has poor weldability, because its alloy element content is increased to improve its strength. In the case of the resistance spot welding of ultra-high tensile steel, it has been reported that the proper welding condition area is reduced and interfacial fracture and partial interfacial fracture occur in the weld zone. Therefore, research into the welding quality judgment that can predict the defect and quality in real time is being actively conducted. In this study, the dynamic resistance of the weld was monitored using the secondary circuit process variables detected during resistance spot welding, and the factors necessary for the determination of the welding quality were extracted from the dynamic resistance pattern. The correlations between the extracted factors and the weld quality were analyzed and a regression analysis was carried out using highly correlated pendulums. Based on this research, a regression model that can be applied to the field was proposed.

• Proceedings of the KWS Conference
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• 1998.10a
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• pp.129-132
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• 1998

The dynamic resistance monitoring in primary circuit or T/C is one of the important issues in that in-process and real time quality assurance of resistance spot weld is needed to increase the product reliability. It is well known that tile dynamic resistance curve gives us very useful information about nugget growth and weldability. In the present paper, a new dynamic resistance detecting method is presented as a practical manner of weld quality assurance using instantaneous current and voltage measured by primary circuit. Primary dynamic resistance patterns are basically similar to those of the secondary, but there is evident advantage such as no extra devices are needed to obtain the quality assurance index and eventually feedback control will be possible caused by T/C based monitoring system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.679-682
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• 2002

Resistance spot welding using air gun has been used for joining the sheet metal in automotive manufacturing process. Although air gun has many advantages, it also has the limitation to control the pressure as a factor to improve weld quality. In this study, we apply servo gun using servo motor to resistance spot welding and find the relationship between welding pressure and welding quality. Trough the experiment to change welding pressure during the welding cycle, we can make it clear that the change of welding pressure is greatly influence on the welding quality. To get in a. using response surface methodology, drew out the optimal welding pressure profile for welding quality progresses. We made an optimal profile of welding pressure which improves welding quality using response surface methodology.

• Journal of Welding and Joining
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• v.31 no.1
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• pp.43-50
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• 2013

The spot welds of Transformation Induced Plasticity (TRIP) steels are prone to interfacial failure and narrow welding current range. Hard microstructures in weld metal and heat affected zone arenormally considered as one of the main reason to accelerate the interfacial failure mode. There fore, detailed observation of weld microstructure for TRIP steels should be made to ensure better weld quality. However, it is difficult to characterize the microstructure, which has similar color, size, and shape using the optical or electron microscopy. The atomic force microscope (AFM) can help to analyze microstructure by using different energy levels for different surface roughness. In this study, the microstructures of resistance spot welds for AHSS are analyzed by using AFM with measuring the differences in average surface roughness. It has been possible to identify the different phases and their topographic characteristics and to study their morphology using atomic force microscopy in resistance spot weld TRIP steels. The systematic topographic study for each region of weldments confirmed the presence of different microstructures with height of 350nm for martensite, 250nm for bainite, and 150nm for ferrite, respectively.

• Journal of Welding and Joining
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• v.19 no.4
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• pp.379-383
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• 2001

Resistance spot welding has been widely used in the sheet metal joining processes because of low cost, high productivity and convenience. Recently, automobile and aerospace industries are trying to replace partly steel sheets with aluminum alloy sheets. But in the case of dissimilar materials, to apply resistance spot welding has been known to be very difficult owing to the effect of melting temperature. On this study, an effort was made to apply spot welding of dissimilar sheet metals, 2024 aluminum alloy and zinc coated steel sheet, evaluate the spot weld quality with tensile-shear strength test and nondestructive evaluation technique, C-scan image methodology. In this study results, as the current below 11 kA, melting of materials is not achieved well. Also as the current exceeds to 13.5 kA, the more spatters happen at welded zone and tensile-shear strength lowered. So, the feasibility of C-scan image technique proposed in the study is found to be suitable evaluation method for resistance spot weldability.