• 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.

• Transactions on Electrical and Electronic Materials
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• 제8권1호
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• pp.11-14
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• 2007

Consumables used in Chemical Mechanical Polishing (CMP) have been played important role to improve quality and productivity. Since the properties of consumables constantly change with various reasons, such as shelf time, manufactured time, lot to lot variation from supplier and so on, CMP results are not constant during the process. Also, CMP process results are affected by multiple sources from wafer, conditioner, pad and slurry. Therefore, multiple sensing systems are required to monitor CMP process variation. In this paper, the authors focus on development of monitoring system for CMP process which consist of force, temperature and displacement sensor to measure the signal from CMP process. With monitoring systems mentioned above, complex CMP phenomena can be investigated more clearly.

• 한국공작기계학회논문집
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• 제11권3호
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• pp.39-44
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• 2002

As laser cutting process is widely used in industry, an automated on-line process control system has become very important. In this paper, development of a laser cutting monitoring system, which is regarded as the fundamental step toward automation of the process, is presented. Acoustic emission and an artificial neural network were used for the monitoring system. With given process Parameters including laser power and scanning speed the system can predict the suitability of laser beam for the cutting or a stainless steel (STS304) plate.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2014년도 추계학술대회 논문집
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• pp.739-742
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• 2014

In the process of MLCC manufacturing, MLCC stacking process is the key process of making high quality MLCC. Since MLCC is small components, the entire process of MLCC stacking process is minute and sensitive to micro errors. To prevent micro error, we suggest condition-based monitoring which quantifies error based on feature extraction and quantifying error method. As results, it has been shown that the suggested algorithm has effectiveness of condition based monitoring of MLCC stacker.

• Journal of Welding and Joining
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• 제28권4호
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• pp.81-86
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• 2010

In resistance spot welding, regardless of the optimal condition, bad weld quality was still produced due to complicated manufacturing processes such as electrode wear, misalignment between the electrode and workpiece, poor part fit-up, and etc.. Therefore, the goal of this study was to measure the process signal which contains weld quality information, and to develop the process fault monitoring system. Welding force signal obtained through variety experimental conditions was analyzed and divided into three categories: good, shunt, and poor fit-up group. And then a monitoring algorithm made up of an artificial neural network that could estimate the process fault of each different category based on pattern was developed.

• 한국컴퓨터정보학회논문지
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• 제18권3호
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• pp.107-118
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• 2013

본 논문에서는 반도체 식각 공정 모니터링 시스템을 개발한다. 반도체 산업은 첨단 산업 중, 전자제품의 필수 부품을 생산하는 대표적인 고부가가치 산업으로, 세계 각국에서 치열한 개발 경쟁을 벌이고 있다. 이에 따라 반도체 제품의 품질과 특성, 그리고 생산성을 향상하기 위한 많은 연구들이 진행되고 있는데, 공정 모니터링 기술이 이에 해당한다. 실제로 반도체 회로를 형성하는 식각 공정에서의 불량은 큰 피해를 야기 시키므로, 공정을 상세히 모니터링 할 수 있는 시스템의 개발이 필요하다. 본 논문에서 기술하는 반도체 식각 공정 모니터링 시스템은 플라즈마를 이용한 건식식각 공정을 상세하게 관찰 분석하여 관리자에게 피드백하고, 설정된 시나리오에 맞게 자동으로 공정을 제어하여 공정 자동화 효율을 극대화한다. 실시간으로 모니터링을 수행하고 그 결과를 즉각적으로 시스템에 반영한다. 관리자는 시스템에서 제공하는UI(User Interface)를 통해 공정의 현재 상태를 진단할 수 있다. 시스템은 관리자가 사전에 작성한 공정 시나리오를 따라 공정을 자동으로 제어하고, 공정중단 시점을 효율적으로 찾아내어 생산 효율을 높인다.

• 한국생산제조학회지
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• 제7권3호
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• pp.14-21
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• 1998

The in-process detection of the state of cutting tool is one of the most important technical problem in Intelligent Machining System. This paper presents a method of detecting the state of cutting tool in turning process, by using Artificial Neural Network. In order to sense the state of cutting tool. the sensor fusion of an acoustic emission sensor and a force sensor is applied in this paper. It is shown that AErms and three directional dynamic mean cutting forces are sensitive to the tool wear. Therefore the six pattern features that is, the four sensory signal features and two cutting conditions are selected for the monitoring system with Artificial Neural Network. The proposed monitoring system shows a good recogniton rate for the different cutting conditions.

• 한국공작기계학회논문집
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• 제11권2호
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• pp.103-111
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• 2002

Out of all metal-cutting process, the hole-making process is the most widely used. It is estimated to be more than 30% of the total metal-cutting process. It is therefore desirable to monitor and detect drill wear during the hole-drilling process. One important aspect in controlling the drilling process is monitoring drill wear status. There are two systems, Basic system and Online system, to detect the drill wear. Basic system comprised of spindle rotational speed, feed rates, thrust torque and flank wear measured by tool microscope. Outline system comprised of spindle rotational speed feed rates, AE signal, flank wear area measured by computer vision, On-line monitoring system does not need to stop the process to inspect drill wear. Backpropagation neural networks (BPNs) were used for on-line detection of drill wear. The output was the drill wear state which was either usable or failure. This paper deals with an on-line drill wear monitoring system to fit the detection of the abnormal tool state.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2008년도 춘계학술대회 논문집
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• pp.434-435
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• 2008

An in-situ monitoring technique for deposition process of CdS buffer layer was developed in this work. A quartz crystal microbalance (QCM) was used to measure the frequency change during the CdS deposition process and the relation ship between frequency change and film thickness and optical transmittance was investigated. The film thickness shows a linear relationship with frequency change, demonstrating that frequency change measured by QCM can be used a in-situ monitoring tool for CdS deposition process.