• Journal of the Korean Data and Information Science Society
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• 제18권3호
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• pp.773-782
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• 2007

The statistical process control charts are very extensively used for monitoring of process mean, deviation, defect rate or reject rate. In this paper we consider a control chart to monitor the process reject rate in the high yield process, which is based on the observed cumulative probability of the number of items inspected until r defective items are observed. We first propose selection of the optimal value of r in the CPC-r charts, and also consider the usefulness of the chart in high yield process such as semiconductor or TFT-LCD manufacturing process.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.387-390
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• 1997

Grinding process takes a long time that grinding machine is setted properly. It is difficult for user to judge correctly the abnormal states generated in grinding process. Air grinding has to be reduced for the improvement of productivity. In addition, it is important to monitor the dressing and the grinding process so that the grinding working maintains optimal grinding conditions. In this study, the monitoring system using the acoustic emission is developed to monitor these processes continuously. This system was able to reduce the preparation as well as the machine setting time in grinding operation.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2003년도 봄 학술발표회 논문집
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• pp.781-788
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• 2003

It is an essential process to predict behaviors of ground and structure to seek economical efficiency and stability on the given environment. Predictions are conducted through analysis process of ground and structure. For these analyses, exact and quick acquisition of measuring data is required. But we face many difficulties in data acquisition stages due to the conditions of construction site. Therefore development of a powerful and effective monitoring system that can manage the integration of database and the implementation of measuring process in real time is strongly desired. This article shows an actual example of application of internet based monitoring system compared with the conventional monitoring system.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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• pp.1386-1390
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• 2007

This paper presents the equipment condition monitoring technology for the process or the equipment using statistical techniques. The equipment condition monitoring system consists of an empirical model to estimate the expected sensor values of process variables and a diagnose model to detect the abnormal condition and to identify the root source of the problem. The empirical model is constructed by the analysis of historic data. The diagnose model uses the sequential probability ratio test (SPRT) technique. The monitoring system was tested with real operating data acquired from the Reactor Coolant Pump Seal in the Nuclear Power Plant. It can detect the system degradation or failure at the early stage since it is able to catch the subtle deviation of process variables from normal condition.

• 한국기계가공학회지
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• 제11권5호
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• pp.142-147
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• 2012

Machining tool conditions directly affect to quality of product and productivity of manufacturing. Many researches performed for tool condition monitoring in machining process to improve quality and productivity. Conventional methods use characteristics of signal for cutting force, motor current consumption, vibration of machine tools and machining sound. Recently, diameter of machining tool is become smaller for minimizing of mechanical parts. Tool condition monitoring using conventional methods are relatively difficult because micro machining using small diameter tool has low machining load and high cutting speed. These days, the direct monitoring for tool conditions using vision system is performed actively. But, vision system is affected by external conditions such as back ground of image and illumination. In this study, minimizing technology of external conditions using distribution analysis of image data are developed in micro machining using small diameter drill and tap. The image data is gathered from vision system. Several sets of experiment results are performed to verify the characteristics of the proposed machining technology.

• Journal of information and communication convergence engineering
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• 제3권4호
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• pp.187-190
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• 2005

High aspect ratio via-hole etching process has emerged as one of the most crucial means to increase component density for ULSI devices. Because of charge accumulation in via-hole, this sophisticated and important process still hold several problems, such as etching stop and loading effects during fabrication of integrated circuits. Indeed, the concern actually depends on accumulated charge. For monitoring accumulated charge during plasma etching process, charge-up monitoring sensor was fabricated and tested under some plasma conditions. This paper presents a neural network-based technique for analyzing and modeling several electrical performance of plasma charge-up monitoring sensor.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2005년도 추계종합학술대회
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• pp.303-306
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• 2005

High aspect ration via-hole etching process has emerged as one of the most crucial means to increase component density for ULSI devices. Because of charge accumulation in via hole, this sophisticated and important process still hold several problems, such as etching stop, loading effects during fabrication of integrated circuits. Indeed, the concern actually depends on accumulated charge. For monitoring accumulated charge during plasma etching process, charge-up monitoring sensor was fabricated and tested under some plasma conditions. This paper presents a neural network-based technique for analyzing and modeling several electrical performance of plasma charge-up monitoring sensor.

• 한국전기전자재료학회논문지
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• 제21권5호
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• pp.397-401
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• 2008

Most of the topic in PCB industry was about increasing the volume of product for the development of electronics in numerous industrial application area. However, it has been emerged that yield improvement quality manufacturing via detecting any suspicious process in order to minimize the scrapped product and material waste. In addition, recently, restriction of hazardous substances (RoHS) claims that electronic manufacturing environment should reduce the harmful chemicals usage, thus the importance of monitoring copper etchant and detecting any mis-processing is crucial for electronics manufacturing. In this paper, we have developed real-time chemical monitoring system using RGB sensor, which is simpler but more accurate method than commercially utilized oxidation reduction potential (ORP) technique. The developed Cu etchant monitoring system can further be utilized for copper interconnect process in future nano-semiconductor process.

• 반도체디스플레이기술학회지
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• 제20권3호
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• pp.27-31
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• 2021

VI probe, which is one of various in-situ plasma monitoring sensor, is frequently used for in-situ process monitoring in mass production environment. In this paper, we correlated the plasma etch results with VI probe data with the small amount of gas flow rate changes to propose usefulness of the VI probe in real-time process monitoring. Several different sized contact holes were employed for the etch experiment, and the etched profiles were measured by scanning electron microscope (SEM). Although the shape of etched hole did not show satisfactory relationship with VI probe data, the chamber status changed along the incremental/decremental modification of the amount of gas flow was successfully observed in terms of impedance monitoring.

• 한국정밀공학회지
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• 제13권11호
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• pp.57-63
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• 1996

Monitoring of grinding troble occurring during the process is classified into the quantitative data which depends upon a sensor and the qualitative knowledge which relies upon an empirical knowledge. Since grinding operation is highly related with a large amount of functional parameters, it is actually deficulty in copying wiht the grinding troubles through the process. To cope with grinding trouble, it is an effective monitoring systems when occurring the grinding process. The use of neural networks is an effective method of detection and/or monitroing on the grinding trouble. In this paper, four parameters which are derived from the AE(Acoustic Emission) signatures are identified, and grinding monitoring system utilized a back propagation learning algorithm of PDP neural networks is presented.