• Journal of Institute of Control, Robotics and Systems
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• v.10 no.11
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• pp.1100-1106
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• 2004

In this report, a self-organizing fuzzy neural network is proposed to control chemical feeding, which is one of the most important problems in water treatment process. In the case of the learning according to raw water quality, the self-organizing fuzzy network, which can be driven by plant operator, is very effective, Simulation results of the proposed method using the data of water treatment plant show good performance. This algorithm is included to chemical feeder, which is composed of PLC, magnetic flow-meter and control valve, so the intelligent control of chemical feeding is realized.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.934-938
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• 1989

This paper considers the model predictive control (MPC) problems in nonlinear processes or systems. The MPC method determines the control law such that the predicted output based on the identified process model is equal to the reference output which consists of both the process output at current time and the setting value called as the command generator. In this paper, the nonlinear MPC software for a chemical reactor is developed and analized from the point of view of practical applications.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1477-1485
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• 2018

There are two major issues for activated sludge process in sewage treatment plant. One is how to make sewage be more clean and the other is the energy saving in sewage treatment process. The major monitoring sewage qualities are chemical oxygen demand, phosphorus, nitrogen, suspended solid in effluent. These are transmitted to the national TMS(Telemetry Monitoring System) at every hour. If these exceed the environmental standard, the environmental charges imposed. So, these water qualities are to be controlled below the environmental standard in operation of sewage treatment plant. And recently, the energy saving is also important in process operation. Over 50% energy is consumed in blowers and motors for injection oxygen into aeration tank. So, with the water qualities to be controlled below the environmental standard, the energy saving also is to be accomplished for efficient plant management. Almost researches are aimed to control water quality without considering energy saving. AI techniques have been used for control water quality. AI modeling simulator provided the optimal control inputs(blower speed, waste sludge, return sludge) for control water quality. Blower speed is the main control input for activated sludge process. To make sewage be more clean, the excessive blower speed is supplied, but water quality is not better than the previous. In results, non necessary energy is consumed. In this paper we propose a new method that the energy saving also is to be accomplished with the water qualities to be controlled below the environmental standard for efficient plant management. Water qualities in only aeration tank are used the inputs of fuzzy models. Outputs of these models are chemical oxygen demand, phosphorus, nitrogen, suspended solid in effluent and have the environmental standards. In test, we found this method could save 10% energy than the previous methods.

• Proceedings of the Korean Society for Quality Management Conference
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• 2007.04a
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• pp.302-309
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• 2007

To conduct statistical process control needs the assumption that the process data are independent. However, most of chemical processes, like a semi-conduct processes do not satisfy the assumption because of autocorrelation. It causes abnormal out of control signal in the process control and misleading process capability. In this study, we introduce that Shore's method to solve the problem and to find the optimal subgroup size to estimate variance for AR(l) model. Especially, we focus on finding an actual subgroup size for small samples using simulation. It may be very useful for statistical process control to analyze process capability and to make a Shewhart chart properly.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2017.11a
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• pp.337-338
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• 2017

지난 60년간 일본, 한국, 중국은 물론이고 아시아에서의 공정 산업은 크게 성장했다. 그 발전과정에서 다양한 사고들을 겪고 극복해내는 과정이 있었으며, 최근 한국의 화학물질관리법을 포함하여 안전 기술 및 안전 관리에 많은 진전 또한 있었다. 이 발표의 서두에서는 한국의 공정산업의 역사적 발전에 대해 뒤돌아보며 당면 과제들에 대한 논의를 전개하고자 한다. 장기적인 경제발전의 일환으로 중화학공업 육성을 표방하며, 초기 단계에 정부주도의 적극적인 산업 발전 계획을 수립해 산업의 성장을 주도하였으며, 1990년대에는 어려움을 극복하기 위해 시장 중심의 구조 조정이 도입되었다. 지난 30년 동안 한국사회에서는 가스 폭발, 건물 붕괴, 화물 및 여객선의 사고를 비롯한 치명적인 사고들이 있었다. 이러한 사고 후에는 필연적으로 안전 정책 및 법률에 중요한 발전이 있었는데, 가장 최근의 것은 2012년 유독 가스 배출 사고 이후 화학물질관리법(Chemical Control Act)을 시행한 것이다. 또한 앞으로 20년간 (2036 년까지) 다양한 구성요소의 수준을 정량화할 수 있는 지속 가능성 개념에 대한 강한 요구가 있음은 주지의 사실이다. 지속 가능성의 새로운 패러다임은 에너지, 경제 및 환경의 전통적인 구성 요소로 구성된다. 더불어 지속 가능성은 안전, 보안 및 세계화(globalization)를 다루어야 한다. 미래의 지속 가능성 개념은 이러한 6가지 구성 요소 모두를 하나의 기능으로 정량적으로 통합할 것이다. 특히 이 작업에 대한 강력한 리더십은 화학 공정 산업에서 절대적으로 부족한 현실이기에, 이러한 기능의 통합과 특화된 교육 및 훈련에 대해 한국의 사례와 해외에서의 글로벌 응용 프로그램에 대란 논의를 통해 본 발표는 향후의 발전방향과 비전에 대해 논의하고자 한다.

• Korean Chemical Engineering Research
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• v.50 no.5
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• pp.830-836
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• 2012

Dead times appear often in describing process dynamics and raise some difficulties in simulating process dynamics or analyzing process control systems. To relieve these difficulties, it is needed to approximate the infinite dimensional dead time by the finite dimensional transfer function and, for this, the Pade approximation method is often used. For the accurate approximation of the dead time, high order Pade approximation is needed and the high order Pade approximation is not easy to memorize and is not stable numerically. We propose a method based on the continued fraction expansion that provides the same transfer functions. The method is excellent numerically as well as systematic to be memorized easily. It can be used conveniently for the process control lecture and computations.

• Journal of the Korean Society of Safety
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• v.36 no.3
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• pp.24-30
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• 2021

Heat is generated during the synthesis and mixing process of chemical compounds due to a change in activation energy during the reaction. A runaway reaction occurs when sufficient heat is not removed during the heat control process within a reactor, rapidly increasing the temperature, reaction speed, and rate of heat generation inside the reactor. A risk assessment was executed using an RC-1 (Reaction Calorimeter) during Friedel-Crafts acylation. Friedel-Crafts acylation runs the risk of rapid heat generation during Active Pharmaceutical Ingredient (API) manufacturing; it was used to confirm the risk of a runaway reaction at each synthesis stage and during the mixing process. This study used experimental data to develop a safety efficiency improvement plan to control the risks of runaway and other exothermic reactions, which was implemented at the production site of a chemical plant.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.1
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• pp.33-40
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• 2010

Because sampling interval for data collection tends to be short compared with the overall processing time, in chemical process, instrumental process related tanks or furnace collected data have a significant autocorrelation. Insufficient control technique and frequent control actions cause unstable condition of the process. Traditional control charts which were developed based on iid (independently and identically distributed) among data cannot be applied on the existence of autocorrelation. Also unstable process is difficult to identity or diagnose. Because large-scale process has a lot of measurable variables and multi-step-structures among data, it is difficult to find relation between measurable variables and nonconformity. In this paper, we suggested an appicable model to diagnose the process and to find relation between measurable variables (CTQ) and nonconformity in the process having autocorrelation, unstable condition frequently, a lot of measurable variables, and multi-step-structure. And we applied this model to real process, to verify that the process engineers could easily and effectively diagnose the process and control the nonconformity.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.289-301
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• 2003

In this paper, we propose Shewhart control chart and EWMA control chart using the autocorrelated data which are common in chemical and process industries and lead to increase the number of false alarms when conventional control charts are applied. The effect of autocorrelated data is modeled as a autoregressive process, and canonical analysis is used to reduce the dimensionality of the data set and find the canonical variables that explain as much of the data variation as possible. Charting statistics are constructed based on the residual vectors from the canonical variables which are uncorrelated over time, and the control charts for these statistics can attenuate the autocorrelation in the process data. The charting procedures are illustrated with a numerical example and simulation is conducted to investigate the performances of the proposed control charts.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.3
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• pp.289-296
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• 2001

This paper proposes multivariate control chart for autocorrelated data which are common in chemical and process industries and lead to increase in the number of false alarms when conventional control charts are applied. The effect of autocorrelated data is modeled as a vector autoregressive process, and canonical analysis is used to reduce the dimensionality of the data set and find the canonical variables that explain as much of the data variation as possible. Charting statistics are constructed based on the residual vectors from the canonical variables which are uncorrelated over time, and therefore the control charts for these statistics can attenuate the autocorrelation in the process data. The charting procedures are illustrated with a numerical example and Monte Carlo simulation is conducted to investigate the performances of the proposed control charts.