• Korean Chemical Engineering Research
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• v.44 no.5
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• pp.425-434
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• 2006

The operability and productivity of continuous processes, especially in petrochemical industries have made remarkable improvement during the past twenty years through advanced process control (APC) typified by model-based predictive control. On the other hand, APC have not been actively practiced in industrial batch processes typified by batch polymerization reactors. Perhaps the main cause for this has been the lack of reliable batch process APC techniques that can overcome the unique problems in industrial batch processes. Recently, some noteworthy progress is being made in this area. New high-performance batch process control techniques that can accommodate and also overcome the unique problems of industrial batch processes have been proposed on the basis of iterative learning control (ILC). In this review paper, recent advancement in the batch process APC techniques are presented, with a particular focus on the variations of the so called Q-ILC method, with the hope that they are widely practiced in different industrial batch processes and enhance their operations.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.875-880
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• 2015

Traditional semiconductor process control has been performed through statistical process control techniques in a constant process-recipe conditions. However, the complexity of the interior of the etching apparatus plasma physics, quantitative modeling of process conditions due to the many difficult features constraints apply simple SISO control scheme. The introduction of the Advanced Process Control (APC) as a way to overcome the limits has been using the APC process control methodology run-to-run, wafer-to-wafer, or the yield of the semiconductor manufacturing process to the real-time process control, performance, it is possible to improve production. In addition, it is possible to establish a hierarchical structure of the process control made by the process control unit and associated algorithms and etching apparatus, the process unit, the overall process. In this study, the research focused on the methodology and monitoring improvements in performance needed to consider the process management of future developments in the semiconductor manufacturing process in accordance with the age of the APC analysis in real applications of the semiconductor manufacturing process and process fault diagnosis and control techniques in progress.

• 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).

• Journal of the Semiconductor & Display Technology
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• v.15 no.4
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• pp.27-32
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• 2016

In recent years, various researches have been conducted to improve process yields in accordance with miniaturization of semiconductor. APC(Advanced Process Control) is considered one of the methods to increase in process yields. APC is a process control technology that maintains optimal process conditions and improves the reliability of results by controlling and formulating the relationship among the various process parameters and results. We built up an optical diagnostic system with a three-channel spectrometer. The system detects signals those represent the changes of specific emission peaks intensity versus each reference and converts it into MFC control signals to get back the changes to the reference state. Controlling the MFC continues until the specific peak intensity changes into the normal state. Through this device, we tested a APC automatically responding to process changes during the plasma process. We could control gas flow while sputtering process on going and improve uniformity of plasma intensity with this system. Finally, we have got results those enhance the plasma intensity non-uniformity to 7.7% from 15.5%. Also, found unexpected oxygen flow what is estimated to be come out from IGZO target.

• 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 KIEE Conference
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• 2008.07a
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• pp.1673-1674
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• 2008

화력발전소 보일러의 각종 공정은 대부분 비례 적분 미분 제어기에 의해 제어되어 왔다. 이러한 비례 미분 적분 제어기의 최적튜닝은 공정에 있어 가장 중요한 부분 중 하나라고 할 수 있다. 또한 보일러 제어는 다중의 입력과 루프로 구성되어져 있어 이를 튜닝하기가 어려워 현재까지의 최적튜닝은 튜닝전문가의 숙련도에 의해 결정되어져 왔다. 본 논문에서는 고급공정제어기(Advanced Process Control, APC)를 개발하는 과정과 이를 이용해 최종적으로 보일러 제어기에서 제어하고자 하는 대상에 대한 응답특성을 간단한 튜닝을 통해 구현하는 과정에 대하여 설명하고 그 결과를 시뮬레이터를 통해 시험함으로써 검증해 보이고자 한다.

• The KIPS Transactions:PartA
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• v.10A no.1
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• pp.69-74
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• 2003

Accurate process control in the manufacturing industry is essential to survive in the competitive market. Statistical process control (SPC) system has been widely used to satisfy the ever-increasing quality control requirements. However, most commercial products in the market are not flexible, semi-automatic, and difficult to interface with other tools. In this paper, we propose an advanced rSPC (Real-Time SPC) system which is based on the web and supports XML protocol. We also provide a powerful graphic facility and an efficient file system to handle the data in real time. Even though the idea can be applied to any manufacturing system, our system is optimized to the semi-conductor industry and TFT/LCD industry. The system is implemented in C++ and COM/DCOM, and shows a good result.

• Proceedings of the Korean Vacuum Society Conference
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• 2015.08a
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• pp.132-132
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• 2015

Virtual metrology (VM) model based on plasma information (PI) parameter for C4F8 plasma-assisted oxide etching processes is developed to predict and monitor the process results such as an etching rate with improved performance. To apply fault detection and classification (FDC) or advanced process control (APC) models on to the real mass production lines efficiently, high performance VM model is certainly required and principal component regression (PCR) is preferred technique for VM modeling despite this method requires many number of data set to obtain statistically guaranteed accuracy. In this study, as an effective method to include the 'good information' representing parameter into the VM model, PI parameters are introduced and applied for the etch rate prediction. By the adoption of PI parameters of b-, q-factors and surface passivation parameters as PCs into the PCR based VM model, information about the reactions in the plasma volume, surface, and sheath regions can be efficiently included into the VM model; thus, the performance of VM is secured even for insufficient data set provided cases. For mass production data of 350 wafers, developed PI based VM (PI-VM) model was satisfied required prediction accuracy of industry in C4F8 plasma-assisted oxide etching process.

• JSTS:Journal of Semiconductor Technology and Science
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• v.11 no.3
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• pp.135-145
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• 2011

Accurate process characterization and optimization are the first step for a successful advanced process control (APC), and they should be followed by continuous monitoring and control in order to run manufacturing processes most efficiently. In this paper, process characterization and recipe optimization methods with multiple outputs are presented in high density plasma-chemical vapor deposition (HDP-CVD) silicon dioxide deposition process. Five controllable process variables of Top $SiH_4$, Bottom $SiH_4$, $O_2$, Top RF Power, and Bottom RF Power, and two responses of interest, such as deposition rate and uniformity, are simultaneously considered employing both statistical response surface methodology (RSM) and neural networks (NNs) based genetic algorithm (GA). Statistically, two phases of experimental design was performed, and the established statistical models were optimized using performance index (PI). Artificial intelligently, NN process model with two outputs were established, and recipe synthesis was performed employing GA. Statistical RSM offers minimum numbers of experiment to build regression models and response surface models, but the analysis of the data need to satisfy underlying assumption and statistical data analysis capability. NN based-GA does not require any underlying assumption for data modeling; however, the selection of the input data for the model establishment is important for accurate model construction. Both statistical and artificial intelligent methods suggest competitive characterization and optimization results in HDP-CVD $SiO_2$ deposition process, and the NN based-GA method showed 26% uniformity improvement with 36% less $SiH_4$ gas usage yielding 20.8 ${\AA}/sec$ deposition rate.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.28-28
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• 2011

우리나라의 주력산업인 반도체 및 디스플레이의 경우 그 생산 설비의 1/3이상이 진공 장비이며 진공 공정을 통해 만들어진다. 이들 산업 분야에서는 우리나라가 세계 최고의 생산 기술을 가지고 있으므로 자체적인 기술 개발 확보가 중요하다. 최근에는 기존에 개발되어 있는 장비의 성능을 뛰어넘어야 하는 공정 기술력이 요구되면서, 진공 공정 기술 개발이 매우 중요한 이슈가 되었다. 반도체나 디스플레이 산업 등 기존 주력산업의 전후방 산업의 경쟁력 강화 측면에서뿐 아니라 태양전지, LED 등 진공기술을 이용한 신성장 동력 산업의 생산 시스템 경쟁력 확보 측면에서도 진공 공정 기술 개발 중요성은 매우 크다. 지금까지 양산에 적용되는 증착, 식각, 확산 등 진공 공정 운영은, 사전 시험을 통해 얻은 최적 공정의 입력 파라미터들을 정해 놓고 그대로 공정을 진행한 뒤, 생산되어 나오는 제품의 상태를 사후 측정하여 공정 이상 여부를 점검하고 미세 조정하는 형태로 진행되고 있다. 실질적으로 현재 진행 중인 진공 공정에 대한 직접적인 정보가 없으므로 공정 중 발생되는 문제들에 대한 대처는 그 공정이 끝난 후에 이루어지는 상황이다. 공정 미세화 및 대구경화에 따라 기존의 wafer to wafer 제어 개념 보다 발전된 개념으로 센서 기반 실시간 공정 진단 제어 기술의 필요성이 대두되었으며 이를 위한 오류 인식 및 예지기술 (Fault Detection & Classification, FDC) 그리고 이 정보를 이용한 첨단 제어 기술(Advanced Process Control, APC)을 개발하는 노력들이 시작되었다. 한국표준과학연구원에서는 수요기업인 대기업과 장비업체, 센서 개발 중소기업 및 학교 연구소와 공동으로 진공 공정 실시간 측정 진단 제어와 관련된 연구를 하고 있다. 진공 공정 환경측정 기술, 플라즈마 상태 측정 기술, 진공 공정 중 발생하는 오염입자 측정 원천 기술 개발과 이를 구현하기 위한 센서 개발, 화학 증착 소스 및 진공 공정 부품용 소재에 대한 평가 플랫폼 구축, 배기 시스템 진단기술 개발 등 현재 진행되고 있는 기술 개발 내용과 동향을 소개한다. 진공 공정 실시간 측정 기술이 확보되면 차세대 반도체 제작에 필요한 정밀 공정 제어가 가능해지고, 공정 이상에 바로 대응 혹은 예방 할 수 있으며, 여유분으로 필요 이상으로 투입되던 자원(대기시간, 투입 재료, 대체용 장비)을 절감하는 등 생산성을 향상을 기대할 수 있다. 또한 진공 환경에서 이루어지는 박막 증착, 식각 공정 과정에 대한 이해가 높아지고, 공정을 개발하고 최적화하는데 유용한 정보를 제공할 수 있으므로, 기존 장비와 차별화된 경쟁력을 가진 고품위 진공 장비 및 부품 개발에 기여할 수 있을 것으로 기대하고 있다.