• Journal of the Korean Society for Precision Engineering
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• v.13 no.12
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• pp.30-37
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• 1996

On-line process control equipment for CO$_{2}$ laser cutting is not available for industrial applications. The major part of the industrial laser cutting machines are adjusted off-line by highly educated engineers. The quality inspection of the sample is visual and referred to different quality scales. Due to the lack of automation the potential laser users hesitate to implement the cutting method. The first step toward an automation of the process is the development of a process monitoring system and the research is cincentrated on the area of on-line quality monitoring during CO$_{2}$ laser cutting. The method is based on the detection of the emitted light from the cutting front by photo diode. The developed monitoring system consists of the OP Amplifier, A/D convertor, power supply and PC. The signal from the photo diode has been undertaken from Fourier analysis and statistical analysis with real time. The photograph of striation pattern was taken by metallurgical microscope. As a result, it is possible to predict the striation pattern according to the beam traveling speed.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1639-1645
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• 1991

Because of the important role LD converters play in the production of high quality steel, various dynamic models have been attempted in the past by many researchers not only to understand the complex chemical reactions that take place in the converter process but also to assist the converter operation itself using computers. And yet no single dynamic model was found to be completely satisfactory because of the complexity involved with the process. The process indeed involves dynamic energy and mass balances at high temperatures accompanied by complex chemical reactions and transport phenomena in the molten state. In the present study, a mathematical model describing the dynamic behavior of LD converter process has been developed. The dynamic model describes the time behavior of the temperature and the concentrations of chemical species in the hot metal bath and slag. The analysis was greatly facilitated by dividing the entire process into three zones according to the physical boundaries and reaction mechanisms. These three zones were hot metal (zone 1), slag (zone 2) and emulsion (zone 3) zones. The removal rate of Si, C, Mn and P and the rate of Fe oxidation in the hot metal bath, and the change of composition in the slag were obtained as functions of time, operating conditions and kinetic parameters. The temperature behavior in the metal bath and the slag was also obtained by considering the heat transfer between the mixing and the slag zones and the heat generated from chemical reactions involving oxygen blowing. To identify the unknown parameters in the equations and simulate the dynamic model, Hooke and Jeeves parttern search and Runge-Kutta integration algorithm were used. By testing and fitting the model with the data obtained from the operation of POSCO #2 steelmaking plant, the dynamic model was able to predict the characteristics of the main components in the LD converter. It was possible to predict the optimum CO gas recovery by computer simulation

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.609-612
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• 2021

Government agencies and companies are establishing and promoting digital transformation strategies in various industrial fields, and are leading the era of the 4th industrial revolution through successful technological innovation. In this time of change, we can see many stories of global companies Nike and Starbucks as successful examples of digital transformation. These two companies are showing successful results through digital transformation. Domestic companies are also conducting digital innovation based on mobile, cloud, IoT, artificial intelligence, and AR/VR technologies, and are establishing RPA (Robotic Process Automation) processes for high efficiency and high productivity. In this paper, we introduce the 3D digital twin space construction automation process technique using data from the entire construction cycle of design, construction, and maintenance of the construction industry, and look into the digital transformation strategy of the construction industry in the future.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.2
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• pp.132-139
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• 2009

Yield is a very important measure that can expresses simply for productivity and performance of company. So, yield is used widely in many industries nowadays. With the development of the information technology and online based real-time process monitoring technology, many industries operate the production lines that are developed into automation system. In these production lines, the product structures are very complexity and variety. So, there are many multi-variate processes that need to be monitored with many quality characteristics and associated process variables at the same time. These situations have made it possible to obtain super-large manufacturing process data sets. However, there are many difficulties with finding the cause of process variation or useful information in the high capacity database. In order to solve this problem, neural networks technique is a favorite technique that predicts the yield of process for process control. This paper uses a neural networks technique for improvement and maintenance of yield in manufacturing process. The purpose of this paper is to model the prediction of a sub process that has much effect to improve yields in total manufacturing process and the prediction of adjustment values of this sub process. These informations feedback into the process and the process is adjusted. Also, we show that the proposed model is useful to the manufacturing process through the case study.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1998.10a
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• pp.703-711
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• 1998

Due to the highly ocmpetitive and volatile manufacturing environment, the field of operation management has received increasing attention in recent years as having strategic importances. This study is about the korean manufacturing strategy and the factory automain levels on the product-process matrixes. In this paper, after reviewing the researches about manufacturing strategy and product-process matrixes, we proposed a conceptual model for satisfied factory automation levels.

• The Journal of Sustainable Design and Educational Environment Research
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• v.19 no.4
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• pp.78-87
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• 2020

This study proposed the basic data that contributes to inducing an effective construction plan through the application of the 4th industrial technology to construct a school building that can guarantee the five goals of construction management: cost, process, quality, safety, and environmental management. To this end, 3D printing, drones, robot automation, and augmented reality technologies that are highly usable in construction sites were identified for construction workers. As part of this, related literature and research data were investigated. The selected 4th industrial technology was investigated and analyzed on how it was used for cost, process, quality, safety, and environmental management in a detailed school construction process. As a result of the analysis, significant results were found for the application plan of the 4th industrial technology in school construction for cost, process, quality, safety, and environmental management.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1271-1274
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• 1997

The industrial automation market encompasses all aspects of the discrete process in the manufactring industries. Nowadays many manufacturers are increasingly moving to increase plant capacity, and are trying to produce better quality at the lower costs. We have studied a modern projection-automation system to achieve the communication network which makes connection among all of the projection machines and connect them to a central computer. This communication system have to be very flexible and fast. Also we have studied the communication interface for the automatic production system including the hardware elements and the communication software.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1367-1370
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• 2003

PROFIBUS is an open industrial communication network for a wide range of application in manufacturing automation and process control systems. PROFIBUS-DP(Decentralized Peripherals) are mainly used to connect smart automation devices via a fast serial link. PROFIBUS-DP adopts master/slave mechanism for communication service. In this paper, we present an implementation method of the protocol stacks for the master station of PROFIBUS-DP.

• Proceedings of the KWS Conference
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• 2002.05a
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• pp.65-67
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• 2002

The gas metal arc welding(GMAW) is regarded as one of the best candidate for welding automation in industrial joining application. It is important to monitor the weld quality for the high performance of weld automation. The measured analog signal is frequency analyzed by digital signal process method. In order to observe the welding phenomena and control welding condition, arc light, voltage, and current are measured at the same time. They are analyzed and compared with arc sound. for these experiments, a power source of constant voltage characteristics was used in the pure metal transfer mode.

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.1
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• pp.53-60
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• 2000

In this paper, we developed a character recognition system which could be applied to the automation of construction assembling, and testing process of components by the recognition of characters on the components used in industry department. In this system the image information of each component was caught by the CCD camera and then characters on the images were recognized automatically. If we apply the system to the industrial field it will meet the various requirements such as high productivity, low cost and high qualify products and factory automation.