• 한국건축시공학회지
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• 제17권6호
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• pp.559-566
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• 2017

공공공사의 입찰 방식 결정은 공무수행담당자의 경험 및 업무의 편의성 등을 고려하여 결정되고 있는데, 입찰을 위한 방식 결정 과정의 타당성 검증은 이루어지지 못하고 있는 실정이다. 입찰방식의 선정에 있어 또다른 도전과제는 경험위주의 의사결정을 근간으로 하고 있어 새로운 형태의 프로젝트 발주 또는 새로운 형태의 입찰방식 적용 시 그것에 대한 객관적 타당성을 마련할 방법이 쉽지 않다는 점이 있다. 따라서 본 연구는 공공공사 프로젝트 발주 방식 선정에 도움을 줄 수 있는 의사결정모델을 개발하고 이의 활용성을 검토하고자 한다. 본 연구는 계층분석적의사결정기법을 이용하여 모델을 개발하였고 실제 업무 수행 담당자 32명을 통해 검증하였다. 모델 활용결과 32명 중 5명의 모델활용에 일관성이 있었으며, 담당자들은 모델에 전적으로 의존할 수 없다는 사실을 인지하면서도 가이드를 제시해줄 수 있다는 점에서 긍정적 의견을 제시하였다. 이를 통해 본 연구에서 제시한 모델이 향후 새로운 형태의 입찰방식 또는 과제 발생 시 관련 업무 수행자의 업무관련 부담을 줄여주고 객관적인 공무수행에 도움을 줄 수 있을 것으로 기대된다.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2022년도 가을 학술논문 발표대회
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• pp.133-134
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• 2022

Recently, the criteria for assessing industrial accidents have been replaced by the mortality rate. It was found that the number of deaths from excavation work was the highest among construction machinery. The risk assessment is being conducted, however the industrial accident mortality rate has not decreased. Accordingly, this study aims to provide the basic for the create of a risk assessment model specialized in construction work at excavator. It provides absolute value from the risk model which is capable of delivery the probability of a disaster. In addition, we provide a relative risk model that compares the risk through scores between detailed works. The relative risk model is combined by likelihood and severity; the likelihood indicates the frequency of accidents and the severity indicates seriousness of fatal accidents. A variable that reflects the conditions of the construction site was added to the risk assessment model based on past disaster cases. And using the concepts of probability and average, the risk assessment process was quantified and used as an objective indicator. Therefore, the model is expected to reduce disasters by raising the awareness of disasters.

• 한국환경과학회지
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• 제14권12호
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• pp.1155-1161
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• 2005

Anoxic-oxic process were analyzed numerically for the each unit and final TN effluent by Water Quality Management(WQM) model and the results were compared data from these sewage or wastewater treatment plants. No bugs and logic error were occurred during simulation work. All of the simulation results tried to two times were obtained and both results were almost same thus this model has good reappearance. A few of simulation results were deviated with measured data because lack of influent water qualities are reported however simulation results have wholly good relationship with measured data. Also each unit of simulation result was kept good relationship with that of measured data therefore this WQM model has good reliance. Finally, WQM model predicts final TN effluent within ${\pm}4.1\;mg/{\ell}$

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.280-283
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• 2015

Many construction projects have used the building information modeling (BIM) extensively considering data interoperability throughout the projects' lifecycles. However, the current approach, which is to collect the data required to support facility maintenance system (FMS) has a significant shortcoming in that there are various individual pieces of information to represent the performance of the facility and the condition of each of the elements of the facility. Since a heterogeneous external database could be used to manage a construction project, all of the conditions related to the building cannot be included in an integrated BIM-based building model for data exchange. In this paper, we proposed an ontology-based facility maintenance information model to integrate multiple, related pieces of information on the construction project using industry foundation classesbased (IFC-based) BIM data. The proposed process will enable the engineers who are responsible for facility management to use a BIM-based model directly in the FMS-based work process without having to do additional data input. The proposed process can help ensure that the management of FMS information is more accurate and reliable.

• 한국전자거래학회지
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• 제12권3호
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• pp.235-249
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• 2007

워크플로우 시스템은 긴 주기의 프로세스의 실행을 통제하는 소프트웨어 시스템이다. 조직의 구성원들이 프로세스의 실행을 담당하는데, 프로세스의 특정 부분을 누가 수행하는가를 결정하는 작업할당 정책이 워크플로우 시스템에 설계 및 구현되어 있어야한다. 여러 조직들의 작업할당에는 매우 다양한 문제들이 있을 수 있어서, 다양한 여러 문제들을 다 포괄하는 하나의 모델을 고안하는 것은 가능하지 않을 것이다. 본 논문에서는 워크플로우 시스템에서의 작업할당 정책에 대한 보편적인 설계 방법으로서, 각 조직에 주어진 임의의 고려할 사항들에서부터 작업할당 정책들을 정의하기 위한 메타 모델 기반 접근 방법을 제시한다.

• 대한간호학회지
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• 제35권2호
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• pp.323-335
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• 2005

Purpose: The purpose of this study was to examine the problems and relevant variables for effective Organizational Socialization of new nurses, to produce a causal map, to build up a simulation model and to test its validity. Method: The basic data was collected from Sep. 2002 to July 2003. The Organizational Socialization process of new nurses was analyzed through a model simulation. The VENSIM 5.0b DSS program was used to develop the study model. Result: This Model shows interrelation of these result variables: organizational commitment, job satisfaction, job performance, intention of leaving the work setting, decision making ability, and general results of Organizational Socialization. The model's factors are characteristic of organization and individual values, task-related knowledge and skills, and emotion and communication that affects new nurses' socialization process. These elements go through processes of anticipatory socialization, encounter, change and acquisition. The Model was devised to induce effective Organizational Socialization results within 24 months of its implementation. The basic model is the most efficient and will also contribute to the development of knowledge in the body of nursing. Conclusion: This study will provide proper direction for new Nurse's Organizational Socialization. Therefore, developing an Organizational Socialization Process Model is meaningful in a sense that it could provide a framework that could create effective Organizational Socialization for new nurses.

• 한국경영과학회지
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• 제24권2호
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• pp.1-15
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• 1999

This research involves the development and evaluation of a work flow control model for a type of flexible manufacturing system(FMS) called a flexible flow line(FFL). The control model can be considered as a kind of hybrid intelligent model in that it utilizes both computer simulation and neural network technique. Training data sets were obtained using computer simulation of typical FFL states. And these data sets were used to train the neural network model. The model can easily incorporate particular aspects of a specific FFL such as limited buffer capacity and dispatching rules used. It also dynamically adapts to system uncertainty caused by such factors as machine breakdowns. Performance of the control model is shown to be superior to the random releasing method and the Minimal Part Set(MPS) heuristic in terms of machine utilization and work-in-process inventory level.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1992년도 춘계학술대회 논문집
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• pp.306-312
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• 1992

The prevention of roll breakage in hot rolling process is improtant to reduce maintenance cost and production loss. Rolling conditions such as the roll force and torque have been intensively studied to overcome the roll breakage. in the present work, a model for life prediction of work rolls under working condition was developed and discussed. The model consists of stress analysis, crack propagation, wear and fatigue calculation model. Roll life can be predicted by stress, crack depth and fatigue damage calculated from this model. The reliability of stress analysis is backed up by the FEM analysis. From the result of simulation using by pressent model, although the fatigue damage of back up roll reachs 80% of practical limit, that of workroll was less than 40%. In edge section of workroll stress amplification is found by wear and bender effect. We can judge that workroll failures are not due to fatigue damage, crack propagation by bending stress but stress amplification by wear and bender in present working condition.

• Nuclear Engineering and Technology
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• 제49권6호
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• pp.1219-1225
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• 2017

In this work, a scalable algorithm for model calibration in nuclear engineering applications is presented and tested. The algorithm relies on the construction of surrogate models to replace the original model within the region of interest. These surrogate models can be constructed efficiently via reduced order modeling and subspace analysis. Once constructed, these surrogate models can be used to perform computationally expensive mathematical analyses. This work proposes a surrogate based model calibration algorithm. The proposed algorithm is used to calibrate various neutronics and thermal-hydraulics parameters. The virtual environment for reactor applications-core simulator (VERA-CS) is used to simulate a three-dimensional core depletion problem. The proposed algorithm is then used to construct a reduced order model (a surrogate) which is then used in a Bayesian approach to calibrate the neutronics and thermal-hydraulics parameters. The algorithm is tested and the benefits of data assimilation and calibration are highlighted in an uncertainty quantification study and requantification after the calibration process. Results showed that the proposed algorithm could help to reduce the uncertainty in key reactor attributes based on experimental and operational data.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.84-89
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• 2003

Fuzzy controller is one of the succeed controller used in the process control in case of model uncertainties. But it my be difficult to fuzzy controller to articulate the accumulated knowledge to encompass all circumstance. Hence, it is essential to provide a tuning capability. There are many parameters in fuzzy controller can be adapted, scale factor tuning of normalized fuzzy controller is one of the adaptation parameter. Two adaptation methods are implemented in this work on an experimental thermal process, which simulate heating process in liquefied petroleum gases (LPG) recovery process in one of petrochemical industries: Gradient decent (GD) adaptation method; supervisory fuzzy controller. A comparison between the two methods is discussed.