• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.405-413
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• 2022

Since the COVID-19 outbreak, the active utilization of new health care service utilizing the ICT technology and data science such as telemedicine, smart hospital, AI dignosis has been increasingly found. In this study we examined the business model of Amazon healthcare which leads disruptive innovation in U.S. health care industry with the introduction of hybrid model of telemedicin, in-person care and customer-centric online drug delivery, home-use diagnostic kit, characterized by the integrated model combining medical care, drug delivery and the use of diagnostic kit. We showed using the multiproduct competition model that the synergy effect between the Amazon's original business areas and the healthcare business area causes the active market penetration and the increase in the customer value from utilization of the Amazon care. Using Hotelling's spatial competition model, we also showed that the competition in the health care market can be greater when consumer's choice of health care providers are available in telemedicine platform. In the long, run the issue of competition being weakened due to the exit of less competent healthcare providers may arise, to which the policymakers in the charge of fair competition in health care industry should pay attention.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.4
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• pp.65-72
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• 2014

To improve the productivity of manufacturing company, the analysis of loss in shop floor has to be conducted and validated. This paper introduces the downtime tracking module using the pre-developed shop floor information acquisition system. To collect the downtime, it utilized shop floor monitoring information, user-registered downtime event, equipment diagnosis algorithm and operator's input. Also, it provided the user interface for the analysis of downtime. From the results of a pilot study, the usability of developed system was validated.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.5
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• pp.450-457
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• 2004

In this research, the automatic synthesis of knowledge models is proposed. which are the basis of the methods using qualitative models adapted widely in fault diagnosis and hazard evaluation of chemical processes. To provide an easy and fast way to construct accurate causal model of the target process, the Role-Behavior modeling method is developed to represent the knowledge of modularized process units. In this modeling method, Fault-Behavior model and Structure-Role model present the relationship of the internal behaviors and faults in the process units and the relationship between process units respectively. Through the multiple modeling techniques, the knowledge is separated into what is independent of process and dependent on process to provide the extensibility and portability in model building, and possibility in the automatic synthesis. By taking advantage of the Role-Behavior Model, an algorithm is proposed to synthesize the plant-wide causal model, Fault-Causality Graph (FCG) from specific Fault-Behavior models of the each unit process, which are derived from generic Fault-Behavior models and Structure-Role model. To validate the proposed modeling method and algorithm, a system for building FCG model is developed on G2, an expert system development tool. Case study such as CSTR with recycle using the developed system showed that the proposed method and algorithm were remarkably effective in synthesizing the causal knowledge models for diagnosis of chemical processes.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.1
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• pp.78-91
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• 2005

Performance limiting factors (PLFs) derived from 161 drinking water treatment plants (DWTPs), assessed by International Technical Diagnosis & Assistance Center, were analyzed and evaluated in more detail in this study. In order to conduct study, 161 DWTPs were divided into five categories depending on their capacity, and into twelve groups according to processes and facilities. From the results of analysis, PLFs and their distribution ratio derived from each category were significantly different. Filtration was the most important performance limiting process in all DWTPs of five categories, and the PLFs in filtration were backwashing velocity, media configuration, bed depth, and formation of mud-ball. The PLFs in coagulation-flocculation process were found out to be coagulant dosage, mixing speed, mechanical problems, and others in the order of frequency of occurrence. Also, insufficient disinfection ability that is resulted from insufficient hydraulic detention time and improper chlorine dose and injection point, is the most significant among PLFs in a clear well. In the case of sedimentation, inappropriate baffle structure and excessive upward velocity were PLFs. In addition, the results showed that high turbid water and low alkalinity in a rainy season, ferric and manganese ions, and ammonia nitrogen have been contributed significantly on the performance of DWTPs.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.1
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• pp.74-80
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• 1999

Recently, manufacturing work has been transformed to small scale production form with various types to act up to user's expectation from mass production with a little items required in the past. Then FMS using NC type machinaries has been applied actively also in domestic manufacturing line to meet thus tendency, but there are many machining troubles occured during work process not be settled yet. Nowdays high efficiently has been required no less than high precision in grinding work for the improvement of productivity. In this study, to represent more advance FMS can be adapted to thus situation In-process type monitoring method using AE and Current sensors is suggested to investigate the machining condition in grinding process. As results form this experimental study, it is recognized well that grinding conditions and dressing point of in time cab be estimated effectively using monitoring method suggested. Furthermore, surface shape of grinding wheel on voluntary point of in time can be predicted indirectly through the observation and comparison of AE signal waveform obtained as performance of continuous dressing work.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.7
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• pp.117-123
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• 2007

This paper is about the economic analysis of the replacement of electric facilities in the production facilities. As the interest of energy is increasing, the efficiency of facilities become more important. So, in this paper, we diagnosed facilities, especially electric motors, in the plant and calculated the operating efficiency, power loss with the load factor. And when we replace these facilities into high-efficiency motors, we also calculated new energy efficiency, energy loss and economic analysis through capital recovery factor. As a result, we economically proved that using high-efficiency motor is more beneficial than using non-high-efficiency motors in the model process.

• Journal of the Korean Society of Safety
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• v.31 no.4
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• pp.35-41
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• 2016

In order to guarantee the process safety and prevent accidents, the deviations from normal operating conditions should be monitored and their root causes have to be identified as soon as possible. The statistical theories-based method among various fault diagnosis methods has been gaining popularity, due to simplicity and quickness. However, according to fault magnitudes, the scalar value generated by statistical methods can be changed and this point can lead to produce wrong information. To solve this difficulty, this work employs PCA (Principal Component Analysis) based method with qualitative information. In the case study of our previous study, the number of assumed faults is much smaller than that of process variables. In the case study of this study, the number of predefined faults is 19, while that of process variables is 6. It means that a fault diagnosis becomes more difficult and it is really hard to isolate a single fault with a small number of variables. The PCA model is constructed under normal operation data in order to get a loading vector and the data set of assumed faulty conditions is applied with PCA model. The significant changes on PC (Principal Components) axes are monitored with CUSUM (Cumulative Sum Control Chart) and recorded to make the information, which can be used to identify the types of fault.

• Information and Communications Magazine
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• v.24 no.9
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• pp.86-95
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• 2007

사무실과 가정의 컴퓨터, 대중화된 휴대폰 사용 그리고 인터넷으로 특징지어지는 정보통신 기술덕택에 현대인은 어느 정도 시간과 공간의 제약을 극복하고 있다. 그러나, 아직도 현대인은 예전에 비해 가까워진 지구촌을 여러 가지 이동체를 타고 이동을 하여야한다. 특히 현대인에게 있어서 자동차는 가정과 직장을 이어주고 업무 목적지와 휴식을 위한 휴양지를 찾아가기 위한 실질적인 이동 수단으로서 가정과 직장에 이은 또 하나의 정보통신기술이 필요한 중요한 영역이다. 따라서 미래형 자동차는 편의 주행, 쾌적 주행을 제공하고 그리고 안전 주행이 보장되는 지능형 자동차의 수요가 예견되고 있으며 이를 구현하기위해 첨단 정보통신, 전자, 제어기술이 요구되고 있다. [1][5][6] 이상과 같은 지능형 자동차 관련 응용 분야는 위 그림과 같이 자동차 여러 부위에 장착되는 첨단 전장품들에 의해서 구현이 된다. 그러나, 기존의 자동차와 달리 미래형 지능형 자동차에서는 많은 전장품들이 장착됨에따라 소요되는 전원의 용량이 증가하게되어 기존 12V에서 42V 시스템으로 바뀔 예정이다. 또한 각종 센서로부터 정보신호를 받아서 정보처리를 하고 Actuator를 제어하기 위해서 많은 전장품들간에 연결되는 신호선들의 배선이 복잡해짐에따라 생산부서에서의 공정비용이 증가하게된다. 또한 향후 석유 에너지의 고갈에 따른 전기 자동차로의 전환이 예상되는데 위에서 언급된 많은 전자장치들간 신호를 주고 받기위해 차량내 여러부위로 퍼져있는 배선들이 차지하는 무게가 상당하므로 차체의 무게를 가볍게 해야하는 차세대 전기 자동차의 성능 향상을 위해서 효율적인 In Vehicular Network 기술이 요구된다. 또한 향후 자동차에 장착된 많은 전자장치들의 고장 진단 및 내장된 SW를 효율적으로 갱신하기 위해서는 여러 전자장치들이 하나의 버스로 연결되는 In Vehicle network이 필수적이다.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.81-81
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• 2011

현재 국내에서 사용하고 있는 교량구조물의 성능평가방법으로는 크게 공용하중에 대한 내하율을 구하기 위하여 허용응력개념이나 강도설계 개념을 적용한 내하력 평가 기법이 사용되고 있다. 그러나 위의 방법들은 일반적으로 공용연수의 경과에 따른 재료 및 구조적 성능의 손실과 여러 가지 하중 및 환경적 요인들의 불확실성으로 인하여 발생하는 손상 및 열화를 반영하기 어렵다. 그리고 제원 및 재료물성치의 불확실성에 대한 기존 설계 자료의 DB 부족으로 기존의 평가방법에서는 이러한 시간의 경과에 따른 성능저하를 정확히 산정할 수 없어 이론상의 값과 실제 구조물과의 차이로 인한 불확실성이 존재 한다. 이에 본 연구에서는 공용년수 경과에 따른 시설물의 재료 구조적인 성능 및 거동분석 수행, 신뢰성 해석 수행을 바탕으로 교량 안전성 평가의 합리성 및 현실성을 제고하며, 구조 신뢰성 해석을 수행함으로써 실제 구조물의 강도 한계상태에 대한 파괴확률을 산정하고 그에 대응하는 위험도를 평가함으로써 안전성 검토를 수행하였다. 본 실험을 통해 1. 재료 강도, 부재 제원, 긴장력, 작용하중 등에 있어 설계 시 가정과 실제 사용 환경 사이의 변동성이 존재한다는 것을 알 수 있었으며, 2. 연구 수행 결과 일반 정밀진단 및 해석에서는 얻을 수 없는 다양하고 중요한 결과를 산출할 수 있었으며 이러한 연구 결과를 바탕으로 개선된 성능평가 기법이 제안 될 수 있음을 알 수 있었다.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.5
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• pp.520-525
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• 1997

This paper presents a fault detection and diagnosis methodology based on weighted symptom model and pattern matching between the coming fault propagation trend and the simulated one. In the first step, backward chaining is used to find the possible cause candidates for the faults. The weighted symptom model is used to generate those candidates. The weight is determined from dynamic simulation. Using WSM, the methodology can generate the cause candidates and rank them according to the probability. Second, the fault propagation trends identified from the partial or complete sequence of measurements are compared with the standard fault propagation trends stored a priori. A pattern matching algorithm based on a number of triangular episodes is used to effectively match those trends. The standard trends have been generated using dynamic simulation and stored a priori. The proposed methodology has been illustrated using two case studies, and the results showed satisfactory diagnostic resolution.