• 반도체디스플레이기술학회지
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• 제18권1호
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• pp.5-9
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• 2019

Optical emission spectroscopy is used to identify chemical species and monitor the changes of process results during the plasma process. However, plasma process monitoring or fault detection by using emission signal variation monitoring is vulnerable to background signal fluctuations. IR heaters are used in semiconductor manufacturing chambers where high temperature uniformity and fast response are required. During the process, the IR lamp output fluctuates to maintain a stable process temperature. This IR signal fluctuation reacts as a background signal fluctuation to the spectrometer. In this research, we evaluate the effect of infrared background signal fluctuation on plasma process monitoring and improve the plasma process monitoring accuracy by using simple infrared background signal subtraction method. The effect of infrared background signal fluctuation on plasma process monitoring was evaluated on $SiO_2$ PECVD process. Comparing the $SiO_2$ film thickness and the measured emission line intensity from the by-product molecules, the effect of infrared background signal on plasma process monitoring and the necessity of background signal subtraction method were confirmed.

• 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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• 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.

• 산업공학
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• 제25권2호
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• pp.170-177
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• 2012

Process control is essential to operate the semiconductor process efficiently. This paper consider fault classification of semiconductor based cyclic signal for process control. In general, process signal usually take the different pattern depending on some different cause of fault. If faults can be classified by cause of faults, it could improve the process control through a definite and rapid diagnosis. One of the most important thing is a finding definite diagnosis in fault classification, even-though it is classified several times. This paper proposes the method that one-class classifier classify fault causes as each classes. Hotelling T2 chart, kNNDD(k-Nearest Neighbor Data Description), Distance based Novelty Detection are used to perform the one-class classifier. PCA(Principal Component Analysis) is also used to reduce the data dimension because the length of process signal is too long generally. In experiment, it generates the data based real signal patterns from semiconductor process. The objective of this experiment is to compare between the proposed method and SVM(Support Vector Machine). Most of the experiments' results show that proposed method using Distance based Novelty Detection has a good performance in classification and diagnosis problems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.415-418
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• 1996

Etching Process, one of the most important process in semiconductor fabrication, has input control part of which components are pressure, gas flow, RF power and etc., and plasma gas which is complex and not exactly understood is used to etch wafer in etching chamber. So this process has not real-time feedback controller based on input-output relation, then it uses EPD(End Point Detection) signal to determine when to start or when to stop etching. Various type EPD controller control etching process using EPD signal obtained from optical intensity of etching chamber. In development EPD controller we concentrate on compensation of this signal intensity and setting the relative signal magnitude at first of etching. We compensate signal intensity using neural network learning method and set the relative signal magnitude using fuzzy inference method. Potential of this method which improves EPD system capability is proved by experiences.

• 한국생산제조학회지
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• 제19권3호
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• pp.407-413
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• 2010

This paper reports on the research which analyzes acoustic signals acquired in progressive compressing, hole blanking, and burr compacting process. An acoustic sensor was set on the bed of hydraulic press. Acoustic signal is generated from progressive stamping process. First the signal acquired from the unit process; compressing, blanking or compacting, is studied by Fourier Transform and Short Time Fourier Transform. The blanking process emitted ultrasonic signal with more than 20kHz, but the compressing and compacting processes emitted acoustic signals with lower than 10kHz. The combined signals periodically acquired right after the tool grinding were then analyzed. 70-80kHz signals appeared in time-frequency domain, but not in the frequency domain, the magnitude of which was related to the tool wear. Short Time Fourier Transform made up for the Fourier Transform in analyzing the emitted signal for stamping process in the ultrasonic domain.

• 한국기계가공학회지
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• 제9권3호
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• pp.76-82
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• 2010

A laborer always watched a process of production carefully but defective manufactures were inspected after press process. These inspections made a waste of human power and defective manufactures could make a serious damage of press mold. Therefore, AE(Acoustic Emission) system was introduced to prevention of the damage of the press molds, to a real time detection of defective manufactures and to save human power. AE system was introduced to solve this problem which is a detecting defective manufacture on real time and to prevent the damage of the press mold. In this research we get acoustic emission signal in accordance with weight and processing method of press by using AE sensor, Preamplifier, AE board signal board which occurs press processing and it analyzed various signal through using CMD8 software on the time. From the result, we found that the intensity and shape of the signal were changed according to the weight and processing type of the press. By using this special algorithm, it can judge the acoustic signal which occurs from press on real time.

• 대한산업공학회지
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• 제30권2호
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• pp.84-92
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• 2004

A process control procedure is proposed when 100% inspection is performed in a process with excellent capability. Only the incomplete measurement data is assumed to be available, i.e. the specific measurement value of the quality characteristic is not available for each item but it can be determined to be smaller or larger than any prescribed value. In the suggested model, a signal limit is introduced to determine whether the process under study is in control or not. If the quality characteristic of an incoming item exceeds the upper signal or the lower signal limit, the process is determined to be stopped or not by comparing the number of consecutively accepted items with a predetermined threshold number. The procedure is designed based on the type I and II errors. The performance of the model is evaluated by the expected number of items produced under the in-control and out-of-control states until the process is stopped.

• 전기의세계
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• 제19권6호
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• pp.1-7
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• 1970

In this paper, to determine process dynamic characteristics, the correlation method for measuring the impulse response of process using a pseudo-random binary signal as the test signal instead of white noise was studied. The error caused by using the signal of Mesquence signal generator which was built up by the authors was analysed. Experments were performed on the 1st and 2nd order lag systems and the results were in good coincidence with theoretical values. It is expected that applying these results, it may be possible to develop a continuous measuring method adaptable to modern control systems.

• Journal of the Korean Statistical Society
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• 제27권2호
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• pp.221-235
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• 1998

Suppose that an observed process can be written as the additive model of the signal process and the noise process with unknown parameters. In practice the signal process is not directly observed. We consider the problem of estimating parameter from the observation process using the quasi-likelihood method.