• 대한전자공학회논문지SD
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• 제43권3호
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• pp.9-14
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• 2006

본 논문에서는 NBTI 특성 개선을 위한 새로운 BEOL 공정을 제안하였다. 우선 BEOL의 마지막 공정인 수소 금속소결 열처리 공정, 보호막 공정 등이 NBTI에 많은 영향을 끼침을 분석하였다 이를 바탕으로 수소 금속소결 대신 질소 금속소결 공정을 적용하고 보호막 층, 특히 PE-SiN 증착 전에 질소 금속소결공정을 실시하여 NBTI 수명시간을 개선하였다. 제안한 방법을 적용하여도 소자 특성이나 NMOS의 HC 특성이 열화 되지 않음을 분석하여 실제 소자에 적용될 수 있음을 증명하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1505-1509
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• 2005

This paper introduces a new architecture of genetically optimized self-organizing fuzzy polynomial neural networks by means of information granulation. The conventional SOFPNNs developed so far are based on mechanisms of self-organization and evolutionary optimization. The augmented genetically optimized SOFPNN using Information Granulation (namely IG_gSOFPNN) results in a structurally and parametrically optimized model and comes with a higher level of flexibility in comparison to the one we encounter in the conventional FPNN. With the aid of the information granulation, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. The GA-based design procedure being applied at each layer of genetically optimized self-organizing fuzzy polynomial neural networks leads to the selection of preferred nodes with specific local characteristics (such as the number of input variables, the order of the polynomial, a collection of the specific subset of input variables, and the number of membership function) available within the network. To evaluate the performance of the IG_gSOFPNN, the model is experimented with using gas furnace process data. A comparative analysis shows that the proposed IG_gSOFPNN is model with higher accuracy as well as more superb predictive capability than intelligent models presented previously.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.20-20
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• 2000

Back-propagation neural network (BPNN) is the most prevalently used paradigm in modeling semiconductor manufacturing processes, which as a neuron activation function typically employs a bipolar or unipolar sigmoid function in either hidden and output layers. In this study, applicability of another linear function as a neuron activation function is investigated. The linear function was operated in combination with other sigmoid functions. Comparison revealed that a particular combination, the bipolar sigmoid function in hidden layer and the linear function in output layer, is found to be the best combination that yields the highest prediction accuracy. For BPNN with this combination, predictive performance once again optimized by incrementally adjusting the gradients respective to each function. A total of 121 combinations of gradients were examined and out of them one optimal set was determined. Predictive performance of the corresponding model were compared to non-optimized, revealing that optimized models are more accurate over non-optimized counterparts by an improvement of more than 30%. This demonstrates that the proposed gradient-optimized teaming for BPNN with a linear function in output layer is an effective means to construct plasma models. The plasma modeled is a hemispherical inductively coupled plasma, which was characterized by a 24 full factorial design. To validate models, another eight experiments were conducted. process variables that were varied in the design include source polver, pressure, position of chuck holder and chroline flow rate. Plasma attributes measured using Langmuir probe are electron density, electron temperature, and plasma potential.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권8호
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• pp.551-560
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• 2004

In this paper, we propose a new architecture of Self-Organizing Fuzzy Polynomial Neural Networks (SOFPNN) that is based on a genetically optimized multilayer perceptron with fuzzy polynomial neurons (FPNs) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially genetic algorithms (GAs). The proposed SOFPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional SOFPNNs. The design procedure applied in the construction of each layer of a SOFPNN deals with its structural optimization involving the selection of preferred nodes (or FPNs) with specific local characteristics (such as the number of input variables, the order of the polynomial of the consequent part of fuzzy rules, and a collection of the specific subset of input variables) and addresses specific aspects of parametric optimization. Through the consecutive process of such structural and parametric optimization, an optimized and flexible fuzzy neural network is generated in a dynamic fashion. To evaluate the performance of the genetically optimized SOFPNN, the model is experimented with using two time series data(gas furnace and chaotic time series), A comparative analysis reveals that the proposed SOFPNN exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literatures.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 추계학술대회 논문집 전기물성,응용부문
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• pp.151-153
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• 2005

Indium tin oxide (ITO) thin film was polished by chemical mechanical polishing (CMP) by the change of process parameters for the improvement of electrical and optical properties of ITO thin film. Light transparent efficiency of ITO thin film was improved after CMP process at the optimized process parameters compared to that before CMP process.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2005년도 추계학술대회 논문집 Vol.18
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• pp.354-355
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• 2005

Indium tin oxide (ITO) thin film was polished by chemical mechanical polishing (CMP) by the change of process parameters for the improvement of electrical and optical properties of ITO thin film. Light transparent efficiency of ITO thin film was improved after CMP process at the optimized process parameters compared to that before CMP process.

• 산업경영시스템학회지
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• 제43권3호
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• pp.61-67
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• 2020

The fourth industrial revolution encourages manufacturing industry to pursue a new paradigm shift to meet customers' diverse demands by managing the production process efficiently. However, it is not easy to manage efficiently a variety of tasks of all the processes including materials management, production management, process control, sales management, and inventory management. Especially, to set up an efficient production schedule and maintain appropriate inventory is crucial for tailored response to customers' needs. This paper deals with the optimized inventory policy in a steel company that produces granule products under supply contracts of three targeted on-time delivery rates. For efficient inventory management, products are classified into three groups A, B and C, and three differentiated production cycles and safety factors are assumed for the targeted on-time delivery rates of the groups. To derive the optimized inventory policy, we experimented eight cases of combined safety stock and data analysis methods in terms of key performance metrics such as mean inventory level and sold-out rate. Through simulation experiments based on real data we find that the proposed optimized inventory policy reduces inventory level by about 9%, and increases surplus production capacity rate, which is usually used for the production of products in Group C, from 43.4% to 46.3%, compared with the existing inventory policy.

• 한국건축시공학회지
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• 제14권5호
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• pp.467-476
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• 2014

최근 건설공사의 기계화로 인한 많은 장비 투입으로 인하여 주변 주민들이 현장 소음에 인한 피해보상을 요구하는 민원이 증가하고 있다. 하지만 현장소음은 예방차원이 아닌 공사 진행과정에서만 제한적으로 관리되며 민원이 발생하고 나서야 대부분의 대처가 이루어지고 있는 실정이다. 또한, 이러한 민원을 해결하기 위해서는 비용과 시간이 과다하게 소요되는데 이는 건설사에 부정적인 영향을 미치게 된다. 이에 본 연구는 착공 전부터 계획된 공사기간과 장비투입 조건을 활용하여 최적 공사비를 찾는 알고리즘을 제안하고 최적 공정표를 도출할 수 있는 스케줄링 프로세스 모델을 개발하는 데 그 목적이 있다. 또한, 이를 활용하여 현장관리자가 공사계획 수립 시 소음발생 여부에 따라 민원이 발생할 때 예측되는 비용정보 및 소음제한에 따른 공사비와 공사기간의 변화 정도를 비교 분석함으로써 보다 합리적이고 효율적인 공사 관리를 수행할 수 있도록 한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.209-213
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• 1987

This paper presents decentralized discrete-time system which is optimized by hierarchical control for process automation via the extended interaction balance method. This proposed method can control general matrix which input matrix is not block diagonalization. Also, this paper shows convergence condition of proposed method.

• 한국전기화학회:학술대회논문집
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• 한국전기화학회 2004년도 수소연료전지공동심포지움 2004논문집
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• pp.219-224
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• 2004