• Proceedings of the KIEE Conference
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• 2004.07c
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• pp.1772-1774
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• 2004

Because the physics occurring during an interruption process is not well known, it is not easy to analyze the characteristics of a self-blast circuit breaker neither theoretically nor experimentally. Fortunately the available computational power and the numerical method improved recently make it possible to predict an interruption process as precisely and fast as possible. Therefore many researches using computational methods have been done for the interruption process of interrupters and applied to extend the information such as thermal and dielectric reignition. In this paper, we have simulated the interruption process of SF6 self-blast circuit breakers with the arc plasma during the fault interruption of a 10 kA current. The CFD program used here is coupled with the electromagnetic field analysis, the radiation model and the effects of turbulence. Through this work, we have get further information about the thermal performance as well as the behavior of the arc. The results have been compared with the measured arc voltage.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.250-255
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• 1993

In this paper, for detection and isolation of instrument and process faults related with steam generator(S/G) in nuclear power plant, two types of observers are designed based on the linearized dynamic model of S/G : a bank of Dedicated Observers (DOS) for instrument faults detection and a bank of Unknown Input Observers(UIO) for process faults detection. And then, they are combined to decide which one between the above two faults occurs. In principle, the failure in ith instrument(process) can be isolated by monitoring the error between the ith output and its estimation obtained from the ith DOS(UIO). It is shown via computer simulations that the present scheme is feasible in finding out the source of a fault.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.12
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• pp.1545-1551
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• 1995

As the modern industrial processes become more complex, it is getting more difficult to model and control the processes. Naturally, an advanced type of DCS(Distributed Control System) with higher level functions is being sought. Advanced DCS is a DCS with advanced functions such as fault diagnosis, GPC(Generalized Predictive Control), NN(Neural Network), and Fuzzy Control. In this thesis, we have studied a fuzzy control algorithm for realizing an advanced DCS. Its algorithm is implemented in a form of function code which is a process control language, being used by the industrial engineers. To verify the realized function code of the fuzzy control, the function code is applied to a continuous casting process of the Pohang Iron & Steel Works in Kwangyang. The rules of the fuzzy control were collected via interviews of the field operators and their operation documents. Finally under a real-time operating system environment, usability of the function code of the fuzzy control is shown via simulation for the continuous casting process.

• Journal of Korean Society for Quality Management
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• v.40 no.3
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• pp.327-336
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• 2012

Purpose: In this study, we research the hurdle rate method to suggest the robust control chart for a contaminated process less vulnerable to fault values than existing control charts. Methods: We produce the results of p, ARL values to compare the performance of two control charts, $\bar{x}-s$ that has been used typically and TM-TS that is suggested by this paper. We implement the simulation focusing on three cases, change of deviation, mean and both of them. Results: We draw a conclusion that the TM-TS control chart has better efficiency than $\bar{x}-s$ control chart over the three cases. Conclusion: We insist that applying TM-TS control chart for a polluted process is more effective than $\bar{x}-s$ control chart.

• Journal of the Semiconductor & Display Technology
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• v.10 no.1
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• pp.101-105
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• 2011

In case of high-tech process industries such as semiconductor and TFT-LCD manufactures, fault of a virtually finished product that is value-added one, since it has gone throughout the most of processes, may give rise to quality cost nearly amount to its selling price and can be a main cause that decreases the efficiency of manufacturing process. This paper proposes a real-time dispatching algorithm for semiconductor manufacturing process with rework. In order to evaluate the proposed algorithm, this paper examines the performance of the proposed method by comparing it with that of the existing dispatching algorithms, based on various experimental data.

• Journal of the Semiconductor & Display Technology
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• v.19 no.2
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• pp.16-21
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• 2020

How accurately reproducible energy is delivered to the wafer in the process of making thin films using PE-CVD (Plasma enhanced chemical vapor deposition) during the semiconductor process. This is the most important technique, and most of the reaction on the wafer surface is made by thermal energy. In this study, we studied the method of monitoring the change of thermal energy transferred to the wafer surface by monitoring the temperature change according to the change of the thin film formed on the showerhead facing the wafer. Through this research, we could confirm the monitoring of wafer thin-film which is changed due to abnormal operation and accumulation of equipment, and we can expect improvement of semiconductor quality and yield through process reproducibility and equipment status by real-time monitoring of problem of deposition process equipment performance.

• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.131-135
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• 2023

Neural network-based time series models called time series neural networks (TSNNs) are trained by the error backpropagation algorithm and used to predict process shifts of parameters such as gas flow, RF power, and chamber pressure in reactive ion etching (RIE). The training data consists of process conditions, as well as principal components (PCs) of optical emission spectroscopy (OES) data collected in-situ. Data are generated during the etching of benzocyclobutene (BCB) in a SF₆/O₂ plasma. Combinations of baseline and faulty responses for each process parameter are simulated, and a moving average of TSNN predictions successfully identifies process shifts in the recipe parameters for various degrees of faults.

• Journal of the Korea Safety Management & Science
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• v.6 no.3
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• pp.237-247
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• 2004

The condition of the manufacturing process in a factory should be diagnosed and maintained efficiently because any unexpected disorder in the process will be reason to decrease the efficiency of the overall system. However, if an expert experienced in this system leaves, there will be a problem for the efficient process diagnosis and maintenance, because disorder diagnosis within the process is normally dependent on the expert's experience. This paper suggests a process diagnosis using data mining based on the collected data from the coil-spring manufacturing process. The rules are generated for the relations between the attributes of the process and the output class of the product using a decision tree after selecting the effective attributes. Using the generated rules from decision tree, the condition of the current process is diagnosed and the possible maintenance actions are identified to correct any abnormal condition. Then, the appropriate maintenance action is recommended using the decision network.

• Journal of the Korean Society of Safety
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• v.35 no.1
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• pp.107-115
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• 2020

This paper introduces the first vital area identification (VAI) process for the physical protection of nuclear power plants (NPPs) during low power and shutdown (LPSD) operation. This LPSD VAI is based on the 3rd generation VAI method which very efficiently utilizes probabilistic safety assessment (PSA) event trees (ETs). This LPSD VAI process was implemented to the virtual NPP during LPSD operation in this study. Korea Atomic Energy Research Institute (KAERI) had developed the 2nd generation full power VAI method that utilizes whole internal and external (fire and flooding) PSA results of NPPs during full power operation. In order to minimize the huge burden of the 2nd generation full power VAI method, the 3rd generation full power VAI method was developed, which utilizes ETs and minimal PSA fault trees instead of using the whole PSA fault tree. In the 3rd generation full power VAI method, (1) PSA ETs are analyzed, (2) minimal mitigation systems for avoiding core damage are selected from ETs by calculating system-level target sets and prevention sets, (3) relatively small sabotage fault tree that has the systems in the shortest system-level prevention set is composed, (4) room-level target sets and prevention sets are calculated from this small sabotage fault tree, and (5) the rooms in the shortest prevention set are defined as vital areas that should be protected. Currently, the 3rd generation full power VAI method is being employed for the VAI of Korean NPPs. This study is the first development and application of the 3rd generation VAI method to the LPSD VAI of NPP. For the LPSD VAI, (1) many LPSD ETs are classified into a few representative LPSD ETs based on the functional similarity of accident scenarios, (2) a few representative LPSD ETs are simplified with some VAI rules, and then (3) the 3rd generation VAI is performed as mentioned in the previous paragraph. It is well known that the shortest room-level prevention sets that are calculated by the 2nd and 3rd generation VAI methods are identical.

• Journal of the Korean earth science society
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• v.44 no.3
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• pp.210-221
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• 2023

The purpose of this study is to evaluate the content knowledge and problem solving process used by pre-service earth science teachers while discriminating faults on geological maps. For this, we collected and evaluated data on fixation duration and gaze plot, while pre-service earth science teachers (N=12) solved the problem on faults interpretation using an eye tracker (Tobii Pro Glass 2 model). The results were as follows. First, most of the pre-service earth science teachers know the concepts of the normal and reverse fault but they do not know the procedural knowledge essential for fault interpretation on geological maps. Second, the pre-service earth science teachers did not draw a geological cross-sectional map to interpret the fault on the geological map and interpreted the fault based on two-dimensional information collected from the geological map rather than three-dimensional information. Therefore, it is essential to improve the teaching and learning environment so that pre-service earth science teachers who will become earth science teachers in the future can learn procedural knowledge essential to comprehend natural phenomena including understanding natural phenomena. The results of this study can substantially help organize a new earth science curriculum or develop materials on teachers' education in the future.