• Proceedings of the KWS Conference
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• 2000.04a
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• pp.303-306
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• 2000

Quality estimation of the weld has been one of the important issues in RSW which is a main process of the sheep metal fabrication in auto-body industry, It was well known that among the various welding process variables, dynamic resistance has a close relation with nugget formation. With this variable, it is possible to estimate the weld quality in real time. In this study, a new quality estimation algorithm is developed with the primary dynamic resistance measured at welding machine timer. For this, feature recognition method of Hopfield neural network is used. Primary resistance patterns are vectorized and classified with five patterns. The network trained by these patterns recognizes the dynamic resistance pattern and estimates the weld quality Because the process variable monitored at the primary circuit is used, it is possible to apply this system to real time application without any consideration of electrode wear or shunt effect.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.791-796
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• 2001

Welding using lasers can be mass-produced in high speed. In the laser welding, performing real-time evaluation 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 sensor. The results of laser welding were classified into five categories such as optimal heat input, little low heat input, low heat input, focus off, and nozzle change. 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. Weld quality prediction program was developed using previous weld results and statistical program which could show the trend of weld quality and signal was developed.

• Journal of Advanced Marine Engineering and Technology
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• v.17 no.2
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• pp.36-43
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• 1993

Real quality and axial void fraction distribution of subcooled refrigerant flow is very important to predict the heat transfer rate and pressure drop in the design of refrigerating system. In the subcooled boiling region, the liquid bulk temperature is still below the corresponding saturation temperature. But beyond the net vapor generation point, bubble detachment is occured actively from the vapor layer formed on the wall. A reliable method to predict the vapor fraction from the liquid bulk temperature is suggested in this paper. And also the actual quality of the subcooled R-113 flow is calculated in the range of 261-1239kg/$m^2$s mass velocity and 10-30K subcooling.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.125-137
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• 2011

This study empirically examined the structural relationships among service quality of internet real estate information web-sites, trust, customer satisfaction and reuse intention. In order to achieve the purpose, survey method was applied using a sample of 293 real estate information web-site users. The results of this study showed that service quality of real estate web-sites had a significant effect on trust and customer satisfaction. And, the trust of web-sites have influenced on customer satisfaction and reuse intention. Finally, the customer satisfaction of estate information web-sites had a significant positive effect on reuse intention.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.723-728
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• 2019

Citizens' distrust of water pollution is very high in tap water that we routinely drink. In addition, water pollution accidents of tap water are difficult to predict and the risk is high, so real-time monitoring and management are needed. Therefore, it is necessary to introduce real-time water quality monitoring using the Internet of things(IoT). Residual chlorine is more persistent and economical than other disinfectants and it is easy to check residual effect, so it is mainly used as a disinfection index in waterworks. It can be monitored in real time by using IoT technology in order to secure the safety of tap water. In this study, we developed smart device for real-time water quality monitoring using amperometry sensor and analyzed its performance.

• Journal of the Korea Safety Management & Science
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• v.20 no.3
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• pp.11-19
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• 2018

This study suggests a model of production information system that can reduce manufacturing lead time and uniformize quality by using DNC S/W as a part of constructing production information management system in the industrial field of the existing marine engine block manufacturing companies. Under the effect of development of this system, the NC machine interface device can be installed in the control computer to obtain the quality information of the workpiece in real time so that the time to inspect the process quality and verify the product defect information can be reduced by more than 70%. In addition, the reliability of quality information has been improved and the external credibility has been improved. It took 30 minutes for operator to obtain, analyze and manage the quality information when the existing USB memory is used, but the communication between the NC controller computer and the NC controller in real time was completed to analyze the workpiece within 10 seconds.

• Journal of Korean Society for Quality Management
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• v.25 no.3
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• pp.119-130
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• 1997

In this paper, we analyze quality loss function(QLF) of Taguchi. Taguchi method of QLF gives more advanced measure process capability than classic capacity(i.e. Cp). We first discuss of QLF and Cp and give one good example of QLF. Because of simplicity of QLF, it is not good fit to a, pp.y in the real field. We suggest interval quantity-loss cost function and total loss cost(TLC) which modify QLF. Also we give one example which can be obtained in the real field.

• Agricultural and Biosystems Engineering
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• v.7 no.1
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• pp.8-12
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• 2006

This study was conducted to develop a real-time internal quality evaluation technique for Korean red ginseng using NIR spectroscopy while they were moving to be graded. Internal qualities of Korean red ginseng were defined by color, amount of white core and cavity in the red ginseng. To evaluate the internal quality, PLS (Partial Least Square) model was developed. Spectrum saturation can be occurred when most red ginseng has a sound internal quality expressed by higher light transmittance ratio, but that could not found in the ginseng of internal white core under the same light situation. And, if spectrum saturation is obtained, it is hard to identify the exact information of internal quality. In order to evaluate of the internal quality regardless of having internal normal core or white core, an integral time controlled method was used to obtain traditional spectrum. This procedure was applied in real-time process when red ginseng was moving to be graded in the line. Among the 450 samples including 223 internal normal ginsengs and 227 internal white core ginsengs, 315 ginsengs (70%) were used to develop a calibration model and 135 ginsengs were spent to validate the model. The result of quality evaluation by the model was very good showing SEP and bias were 0.3573 and 0.0310, respectively, and the accuracy was 95.6%.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.57-60
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• 1999

An optimal control technique designed for simultaneous tracking and quality control for batch processes. The proposed technique is designed by transforming quadratic-criterion based iterative learning control(Q-ILC) into linear quadratic control problem. For real-time quality inferential control, the quality is modeled by linear combination of control input around target qualify and then the relationship between quality and control input can be transformed into time-varying linear state space model. With this state space model, the real-time quality inferential control can be incorporated to LQ control Problem. As a consequence, both the quality variable as well as other controlled variables can progressively reduce their control error as the batch number increases while rejecting real-time disturbances, and finally reach the best achievable states dictated by a quadratic criterion even in case that there is significant model error Also the computational burden is much reduced since the most computation is calculated in off-line. The Proposed control technique is applied to a semi-batch reactor model where series-parallelreactions take place.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.6
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• pp.738-748
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• 2005

Considering pollution source is transferred by discharge, it is very important to analyze the correlation between discharge and water quality. And temperature also influent to the water quality. In this paper, it is used water quality data that was measured DO (Dissolved Oxygen), TOC (Total Organic Carbon), TN (Total Nitrogen), TP (Total Phosphorus) at Dalchun real time monitoring stations in Namhan river. These characteristics were analyzed with the water quality of rainy and nonrainy periods. Input data of the water quality forecasting models that they were constructed by neural network and neuro-fuzzy was chosen as the reasonable data, and water quality forecasting models were applied. LMNN (Levenberg-Marquardt Neural Network), MDNN (MoDular Neural Network), and ANFIS (Adaptive Neuro-Fuzzy Inference System) models have achieved the highest overall accuracy of TOC data. LMNN and MDNN model which are applied for DO, TN, TP forecasting shows better results than ANFIS. MDNN model shows the lowest estimation error when using daily time, which is qualitative data trained with quantitative data. If some data has periodical properties, it seems effective using qualitative data to forecast.