• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1360-1363
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• 1996

EPD(End Point Detection) is used to decide etching degree of layer which must be removed at wafer etching process in plasma etching process which is one of the most important process in semiconductor manufacturing. In this thesis, the method which detects malfunction of etching process in real-time will be discussed. Several EPD signal traces are collected in normal plasma etching condition and used as reference EPD signal traces. Critical points can be detected by applying differentiation and zero-crossing techniques to reference EPD signal. Mean and standard deviation of critical parameters which is memorized from reference EPD signal are calculated and these determine the lower and higher limit of control chart. And by applying statical control chart to EPD signals which are collected in real etching process malfunctions of process are detected in real-time. By means of applying this method to the real etching process we prove our method can accurately detect the malfunction of etching process and can compensate disadvantage of current industrial method.

• 제어로봇시스템학회논문지
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• 제4권4호
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• pp.506-516
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• 1998

In this paper, an algorithm is proposed to detect the malfunction of plasma-etching characteristics using EPD signal trajectories. EPD signal trajectories offer many information on plasma-etching process state, so they must be considered as the most important data sets to predict the wafer states in plasma-etching process. A recent work has shown that EPD signal trajectories were successfully incorporated into process modeling through critical parameter extraction, but this method consumes much effort and time. So Principal component analysis(PCA) can be applied. PCA is the linear transformation algorithm which converts correlated high-dimensional data sets to uncorrelated low-dimensional data sets. Based on this reason neural network model can improve its performance and convergence speed when it uses the features which are extracted from raw EPD signals by PCA. Wafer-state variables, Critical Dimension(CD) and uniformity can be estimated by simulation using neural network model into which EPD signals are incorporated. After CD and uniformity values are predicted, proposed algorithm determines whether malfunction values are produced or not. If malfunction values arise, the etching process is stopped immediately. As a result, through simulation, we can keep the abnormal state of etching process from propagating into the next run. All the procedures of this algorithm can be performed on-line, i.e. wafer to wafer.

• 제어로봇시스템학회논문지
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• 제4권2호
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• pp.246-255
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• 1998

This paper presents a novel method for real-time malfunction detection of plasma etching process using EPD signal traces. First, many reference EPD signal traces are collected using monochromator and data acquisition system in normal etching processes. Critical points are defined by applying differentiation and zero-crossing method to the collected reference signal traces. Critical parameters such as intensity, slope, time, peak, overshoot, etc., determined by critical points, and frame attributes transformed signal-to symbol of reference signal traces are saved. Also, UCL(Upper Control Limit) and LCL(Lower Control Limit) are obtained by mean and standard deviation of critical parameters. Then, test EPD signal traces are collected in the actual processes, and frame attributes and critical parameters are obtained using the above mentioned method. Process malfunctions are detected in real-time by applying SPC(Statistical Process Control) method to critical parameters. the Real-time malfunction detection method presented in this paper was applied to actual processes and the results indicated that it was proved to be able to supplement disadvantages of existing quality control check inspecting or testing random-selected devices and detect process malfunctions correctly in real-time.

• Journal of Advanced Marine Engineering and Technology
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• 제27권1호
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• pp.42-48
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• 2003

In general many engineers can diagnose the fault condition using the abnormal ones among data monitored from a diesel engine, but they don't need the system modelling or identification for the work. They check the abnormal data and the relationship and then catch the fault condition of the engine. This paper proposes the construction of a fault diagnosis engine through malfunction data gained from the data fault detection system of neural networks for diesel generator engine, and the rule inference method to induce the rule for fuzzy inference from the malfunction data of diesel engine like a site engineer with a fuzzy system. The proposed fault diagnosis system is constructed in the sense of the Malfunction Diagnosis Engine(MDE) and Hierarchy of Malfunction Hypotheses(HMH). The system is concerned with the rule reduction method of knowledge base for related data among the various interactive data.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2009년도 추계학술대회 논문집
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• pp.757-758
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• 2009

• 전력전자학회:학술대회논문집
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• 전력전자학회 2018년도 전력전자학술대회
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• pp.267-269
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• 2018

This paper is a study to solve the malfunction of Fire Detection System and to react swiftly in case of fire. if a fire occurs because of malfunction of the fire receiver, it may not be possible to respond appropriately. in order to solve this problem, Fire Detection System using IoT, the manager studied the method of confirming the fire occurrence with mobile phone Application. We propose a wireless Fire Detection System by building a server and a client using a micom and a mobile phone application. This is to reduce the damage caused by the fire.

• 대한기계학회논문집A
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• 제34권10호
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• pp.1529-1535
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• 2010

생산 장비로서 잉크젯 기술의 신뢰성을 증대 시키기 위하여 잉크젯 헤드의 작동 상태를 모니터링하고 이상 유무를 즉시 발견 할 수 있는 소프트웨어 및 하드웨어를 개발 하였다. 잉크젯 헤드의 작동 상태의 측정을 위하여 잉크젯 헤드의 피에조 전기 신호를 사용하였다. 이를 위하여 피에조의 변형량을 간접적으로 측정 할 수 있는 회로를 개발 하였고, 측정된 전기 신호를 사용하여 작동의 불량 여부를 판단 할 수 있도록 소프트웨어 알고리즘을 개발하였다. 또한 다중 노즐 헤드에 적용이 가능하도록 소프트웨어 개발 및 시스템 통합을 수행하였다.

• 한국방재학회 논문집
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• 제10권5호
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• pp.49-54
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• 2010

목조문화재의 화재특성을 보면 화재전파가 빠르고 화재가 발생하면 전소로 이어질 가능성이 큰 특징을 가지고 있다. 그러므로 화재의 예방과 초기 진압을 위해서는 상황을 정확히 인지할 수 있는 기술적인 대응과 더불어 인지된 문제를 조기에 대처할 수 있는 시스템이 필요하다. 이러한 기술을 첨단 유비쿼터스 기술에 의한 상황 감지, 그리고 상황에 따른 빠른 대처 즉, 진압에 활용하기 위해 본 연구에서는 유비쿼터스 센서 네트워크(USN) 기술, 불꽃감지기, 이미지 센서, USN 기반 문화재 방재 응용사례, 오작동 확인시스템 구현 등에 대해서 살펴보고 유비쿼터스형 문화재 방재시스템에 대해 불꽃감지기 오작동 확인시스템에 대해 실험하여 연구결과를 제시하였다.

• Journal of Mechanical Science and Technology
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• 제18권11호
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• pp.1961-1968
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• 2004

The design of a reliable and failsafe control system requires that sensor failures be detected and identified within acceptable time limit so that system malfunction can be prevented. This paper presents a model-based approach to sensor fault detection with applications to vehicle stability control systems. The effectiveness of the proposed method is illustrated through test data-based evaluation. Vehicle test data-based evaluation results show that the proposed fault management scheme can be used for the design of a failsafe VSCs.

• 한국안전학회지
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• 제29권5호
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• pp.54-59
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• 2014

The record type receivers that are operated in large industrial sites have strength in preventing fire. However, because of its long circuit lines and multiple detectors, the receivers are vulnerable to lightning, noise, and breakdown of equipments, resulting in malfunction. In case of malfunctioning of detection circuits of main protection areas, such as electrical room and server room, potential release of gaseous extinguisher agents may lead to property and life damage. In this paper, we present the results on the characteristics of the transponder that initiates the solenoid valves, with respect to various electromagnetic and lightning inflow conditions. Based on the measured data, we analyzed the systematic problems of the transponder. In order to prevent receiver malfunctions, a sequential circuit was configured with two additional transponders and a timer. The circuit was tested with a simulator with preference and delay circuit algorithms.