• 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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1990.04a
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• pp.326-334
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• 1990

A monitoring process of a communication network with two links is analyzed. The Markov process is introduced to compute busy and idle portions of monitoring processor and monitored rate of each link. Inter-idle times and inter-monitoring ties of monitoring processor between two links are respectively computed. A recursive formula is introduced to make the computational procedure rigorous.

• International Journal of Contents
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• v.4 no.4
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• pp.7-11
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• 2008

This paper embodies the agent based cinder monitoring system which supports PDA{Personal Digital Assistant). Monitoring system automatically manages data by using data managing agents such as a state managing agent, a location managing agent, a badness managing agent, a circumstances managing agent, etc, and uses a massive data processing agent to manage massive data. The development of agent based data monitoring system for the stable cinder reuse will be an epoch-making method to develop the process mechanized or manual-labored that widely spreads into the real-time automated process.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.230-235
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• 1997

During laser welding, a laser induced matal vapour and plasuma is formed. The plasma shows strong fluctuation combined with acoustic sound emission. On-line monitoring of the process is possible by measuring and analysing the plasma and acoustic sound emission. This paper introduce the method of on line process monitoring in the laser beam welding and analysis being monitoring signal. The results show the complementary information on the process.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.1
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• pp.43-50
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• 1996

From a manufacturing standpoint it would be desirable to monitor the degradation of drawing die, that is essential for the maintenance of die quality, the evaluation of product integrity and the reducing scrap. Acoustic emission is powerful method in monitoring fine wire drawing process, especially in detecting the die fracture at early stage. Experiments also suggested that acoustic emission sigals contained valuable information regarding the stage of a drawing process such as the surface appearance of products and the condition of lubrication. These informations are AE monitoring techniques a possible tool in monitoring the drawing process operation. In order to approach this, this paper discusses the nature of acoustic emission signal presented which illustrate the effects of wire and die material, lubricants, and drawing speed on the generation and the mean voltage level of acoustic emission signal. From these experimental, results, we understanded controlling factors of acoustic emission generation.

• JSTS:Journal of Semiconductor Technology and Science
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• v.11 no.1
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• pp.1-5
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• 2011

To enter next process control, numerous approaches, including run-to-run (R2R) process control and fault detection and classification (FDC) have been suggested in semiconductor manufacturing industry as a facilitation of advanced process control. This paper introduces a novel type of optical plasma process monitoring system, called plasma eyes chromatic system (PECSTM) and presents its potential for the purpose of fault detection. Qualitatively comparison of optically acquired signal levels vs. process parameter modifications are successfully demonstrated, and we expect that PECSTM signal can be a useful indication of onset of process change in real-time for advanced process control (APC).

• Korean Chemical Engineering Research
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• v.46 no.2
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• pp.233-247
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• 2008

Process monitoring technology is able to detect the faults and the process changes which occur in a process unpredictably, which makes it possible to find the reasons of the faults and get rid of them, resulting in a stable process operation, high-quality product. Statistical process monitoring method based on data set has a main merit to be a tool which can easily supervise a process with the statistics and can be used in the analysis of process data if a high quality of data is given. Because a real process has the inherent characteristics of nonlinearity, non-Gaussianity, multiple operation modes, sensor faults and process changes, however, the conventional multivariate statistical process monitoring method results in inefficient results, the degradation of the supervision performances, or often unreliable monitoring results. Because the conventional methods are not easy to properly supervise the process due to their disadvantages, several advanced monitoring methods are developed recently. This review introduces the theories and application results of several remarkable monitoring methods, which are a nonlinear monitoring with kernel principle component analysis (KPCA), an adaptive model for process change, a mixture model for multiple operation modes and a sensor fault detection and reconstruction, in order to tackle the weak points of the conventional methods.

• Transactions on Electrical and Electronic Materials
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• v.14 no.2
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• pp.71-77
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• 2013

Advanced semiconductor manufacturing technology requires methods to maximize tool efficiency and improve product quality by reducing process variability. Real-time plasma process monitoring and diagnosis have become crucial for fault detection and classification (FDC) and advanced process control (APC). Additional sensors may increase the accuracy of detection of process anomalies, and optical monitoring methods are non-invasive. In this paper, we propose the use of a chromatic data acquisition system for real-time in-situ plasma process monitoring called the Plasma Eyes Chromatic System (PECS). The proposed system was initially tested in a six-inch research tool, and it was then further evaluated for its potential to detect process anomalies in an eight-inch production tool for etching blanket oxide films. Chromatic representation of the PECS output shows a clear correlation with small changes in process parameters, such as RF power, pressure, and gas flow. We also present how the PECS may be adapted as an in-situ plasma arc detector. The proposed system can provide useful indications of a faulty process in a timely and non-invasive manner for successful run-to-run (R2R) control and FDC.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.653-657
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• 2000

The paper describes the contents and results of the national project named "Development of Computer Integrated Product Design for Automation Equipment". It is focussed on the real-time control '||'&'||' monitoring of manufacturing process for automobile rubber parts. Automobile rubber parts industy is one of the typical process that high11 depends upon manufacturing facilities and equipments. So. it requires high cost and engineering technolog) on plant implementation. But most companies of rubber parts industries are small or mid companies that habe weak abilities for plant implementation properly and systematically. Therefore, for upgrading the levelof automation. it is necessar). to dekelope the computer based management and monitoring slsteni that enables to build-up the common base of automation and systemization. 'Through this project. we developed low cost real-time monitoring system for banbun mixing process '||'&'||' mold injection process of rubbcr parts manufacturing, that is composed with DDCU(Distributed Digital Control Unit),signal interfaces to gathering mon~toring terms and speciall\ developed functional sofhare including some algorithm for management '||'&'||' process monitoring

• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.1
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• pp.39-55
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• 2011

Process monitoring has been emphasized for the monitoring of complex system such as chemical processing industries to achieve the efficiency enhancement, quality management, safety improvement. Recently, ICA (Independent Component Analysis) based MSPC (Multivariate Statistical Process Control) was widely used in process monitoring approaches. Moreover, DICA (Dynamic ICA) has been introduced to consider the system dynamics. However, the existing approaches show the limitation that their performances are strongly dependent on the statistical distributions of control variables. To improve the limitation, we propose a novel approach for process monitoring by integrating DICA and LOF (Local Outlier Factor). In this paper, we aim to improve the fault detection rate with the proposed method. LOF detects local outliers by using density of surrounding space so that its performance is regardless of data distribution. Therefore, the proposed method not only can consider the system dynamics but can also assure robust performance regardless of the statistical distributions of control variables. Comparison experiments were conducted on the widely used benchmark dataset, Tennessee Eastman process (TE process), and showed the improved performance than existing approaches.