• Korean Journal of Construction Engineering and Management
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• v.15 no.5
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• pp.127-137
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• 2014

Project Financing (PF) development project is the type which influences national economy and building industry largely because it is exerted by using borrowed money from many kinds of investors and huge amount of financial raising. Many domestic PF projects are focused mainly on the profit maximization lacking in a sufficient feasibility study. Nowadays many projects are suspending due to the global finance debacle and stagnation of real estate industry. Therefore, in this paper, risk factors of PF project are deducted and Key Success Factors (KSFs) are derived through Factor-Analysis and qualified using Fuzzy-AHP method. And through the evaluation of the derived success factors in real projects, a strong correlationship has been identified between the score of each PF success factor and the level of success and/or expected rate of return (ROR). So, the result of this paper can help decision makers of the PF projects make a better decision and give a meaningful guidance in achieving successful PF projects.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6A
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• pp.765-778
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• 2008

Performance Profiles are essential to predict the performance variation over time for the bridge management system (BMS) based on risk management. In general, condition profiles based on experts opinion and/or visual inspection records have been used widely because obtaining profiles based on real performance is not easy. However, those condition profiles usually don't give a good consistency to the safety of bridges, causing practical problems for the effective bridge management. The accuracy of performance evaluation is directly related to the accuracy of BMS. The reliability of the evaluation is important to produce the optimal solution for distributing maintenance budget reasonably. However, conventional methods of bridge assessment are not suitable for a more sophisticated decision making procedure. In this study, a method to compute quantitative performance profiles has been proposed to overcome the limitations of those conventional models. In Bridge Management Systems, the main role of performance profiles is to compute and predict the performance of bridges subject to lifetime activities with uncertainty. Therefore, the computation time for obtaining an optimal maintenance scenario is closely related to the efficiency of the performance profile. In this study, the Response Surface Method (RSM) based on independent and important design variables is developed for the rapid computation. Steel box bridges have been investigated because the number of independent design variables can be reduced significantly due to the high dependency between design variables.

• Journal of the Korea Institute of Building Construction
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• v.10 no.2
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• pp.41-50
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• 2010

This study presented a model that can enable a reliability analysis for the repair and replacement cycle of a building by using background repair and replacement data and expert opinion as foundation data and applying Monte Carlo Simulation. The presented model offers the time of the repair and replacement of building elements for the period of a year, and supports the prediction of repair and replacement and expenses demand in advance while planning the maintenance of a building. In addition, the model will significantly reduce the risks to the building owner with regard to maintenance decisions. In addition, when a person in charge of the maintenance of large-scale building assets is having difficulties making decisions regarding the repair and replacement of existing building elements due to a lack of background data to support a long-term policy on the repair and replacement requirements, an engineering solution that can ensure the adequacy of this is provided. In summary, it can be largely divided into three study results. First, a method of estimating the repair and replacement cycle that can deal with the development of a construction system was developed. Second, a probabilistic methodology that can quantify the risk of the repair and replacement cycle was proposed. Third, the proposed model can be used as a means of supporting designer and constructor in making decisions for the life cycle plan of a building during a construction project.

• Journal of Food Hygiene and Safety
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• v.27 no.4
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• pp.356-365
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• 2012

There have been growing concerns among people about food safety due to insufficient information on foodborne pathogens. In this study, we developed a risk priority of 15 foodborne pathogens. For the priority determination we collected risk profile criteria information from CODEX Alimentarius Commission and developed countries. The basis for criteria we selected from information of surveillance were frequency and severity of disease, frequency of consumption and probability of cross-contamination. We also considered foodborne pathogens which have been managed in developed countries though those pathogens are not currently managed appropriately in Korea. Priorities were divided into three groups following these consideration. The first priority group includes Norovirus, pathogenic E. coli, Salmonella spp, Clostridium botulinum and Listeria monocytogenes. The second priority group includes Vibrio parahaemolyticus, Stapylococcus aureus, Campylobacter jejuni and Bacillus cereus, and the third priority group includes Clostridium perfringens, Yersinia enterocolitica, Shigella spp, Cronobacter sakazakii and Hepatitis A virus. Our results could be applied to prevent foodborne illness from fresh produce.

• Economic and Environmental Geology
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• v.56 no.2
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• pp.155-166
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• 2023

Through COVID-19, the importance of supply chain management of raw material minerals has been maximized. In particular, supply chain management is important for rare metals, which are difficult to manage demand and supply, in order to secure raw materials for the parts and materials industry that Korea is actively promoting. In this study, a system was established and evaluated to select Critical minerals that need to respond to Korea's industrial structure and global risks by quantifying tangible and intangible risk factors. Global Supply Concentration, Supplying country risk, Policy Social Environment Regulation, Domestic Import Instability, Risk responsiveness, Market Scale, Demand Fluctuation and Economic Importance were evaluated as evaluation indicators. The degree of risk and risk impact were quantitatively measured using the criticality matrix-criticality level. After evaluating 40 types of minerals used in domestic new growth businesses, 15 types of Critical minerals(Li, Pt, Co, V, REE, Mg, Mo, Cr, Ti, W, C, Ni, Al, Mn, Si) in Korea were selected. The results are expected to be used to establish policies to strengthen resource security and to make decisions to form a company's raw material portfolio.

• Korean Journal of Construction Engineering and Management
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• v.10 no.1
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• pp.91-101
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• 2009

The factors of uncertainty such as work delay could cause many problems, for example, increase of construction cost and terms of work, and the deterioration of quality. Because of these, the uncertainty risk is regarded as an important management factor to obtain the success of construction project. So, the systematic management plan about the uncertainty factors is needed because it plays an important role in the completion of entire project. And also analysis of some factors which can cause the work delay can be one way of improving construction project's certainty and making it competitive. In this reason, we have to make an effort to set a priority based on analysis of quantitatively numerical value about work delay factors to manage them effectively. Thus, this study aims to suggest the basic data for the effective management and prevention of work delay in steel-frame work which is progressive actively now, along with increasing of demand of high-rise buildings by analyzing each reasons of work delay factors and also by suggesting important management factors that are coded according to each construction work using FMEA method which could give a data about the importance of work delay factors through quantitatively numerical value.

• Korean Journal of Construction Engineering and Management
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• v.14 no.1
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• pp.82-90
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• 2013

In the construction industry, there are so many qualitative factors affecting the performance of a project. So it is crucial to measure the factors in an effective way in order to analyze the interrelationship among the various factors. To improve the performance level of a project, it is also important to identify the most appropriate management practices which are inter-linked with the subject project. The purpose of this study is to develop a project performance management system (PPMS) to quantitatively analyze the variety of project performance data and identify the best management practice to increase the potential level of a particular performance area. Using a comparative statistical method, this study developed a quantification method and web-based computerized system to enhance the usage of the system. The system, however, is still under the validation stage because of the shortage of data set. In the future, when more and more completed project data are stored in the system, the system would play a crucial role in predicting the performance level and matching the best management practice for a subject project. In addition, the system can also be modified as a tool for a business- or industry-level system by incorporating the existing enterprise resource programs.

• Korean Journal of Construction Engineering and Management
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• v.10 no.1
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• pp.102-113
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• 2009

When planning and promoting apartment house development project, it is very important to carry on profitability in planning stage through realistic evaluation and analysis about distributability. Especially, the analysis about project feasibility through forecasting the early distribute rate is crucial stage because it could evaluate overall expecting benefit and feasibility of the project. However, researches and studies related with forecasting profitability and distributabilty of construction development project are insufficient. Also there is a big gap of the standard for evaluating early distribute rate between government and individual corporations. So it is necessary to study about the evaluating early distribute rate. In this point, this study aims to present effective evaluating standard(criteria) which is for forecasting profitability and distribute rate through analyzing various factors and weight of apartment house development projects. This study compared and analyzed examples of the real initial rate of private apartment sale based on the government estimated standard. Among estimated index, omitted items and factors to be additionally considered are combined as 33 detail appraisal contents of 4 parts 9 items by allotting them based on the data about priority of all considered factors.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.27 no.5
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• pp.304-314
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• 2015

We have reviewed the current status of coastal vulnerability index(CVI) to be guided into an appropriate CVI development for Korean coast and applied a methodology into the east coast of Korea to quantify coastal vulnerability by future sea_level rise. The CVIs reviewed includes USGS CVI, sea_level rise CVI, compound CVI, and multi scale CVI. The USGS CVI, expressed into the external forcing of sea_level rise, wave and tide, and adaptive capacity of morphology, erosion and slope, is adopted here for CVI quantification. The range of CVI is 1.826~22.361 with a mean of 7.085 for present condition and increases into 2.887~30.619 with a mean of 12.361 for the year of 2100(1 m sea_level rise). The index "VERY HIGH" is currently 8.57% of the coast and occupies 35.56% in 2100. The pattern of CVI change by sea_level rise is different to different local areas, and Gangneung, Yangyang and Goseong show the highest increase. The land use pattern in the "VERY HIGH" index is dominated by both human system of housing complex, road, cropland, etc, and natural system of sand, wetland, forestry, etc., which suggests existing land utilization should be reframed in the era of climate change. Though CVI approach is highly efficient to deal with a large set of climate scenarios entailed in climate impact assessment due to uncertainties, we also propose three_level assessment for the application of CVI methodology in the site specific adaptation such as first screening assessment by CVI, second scoping assessment by impact model, and final risk quantification with the result of impact model.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.2
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• pp.93-101
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• 2019

The objective of this study is to develop a model which can predict the seismic performance of the slope relatively accurately and efficiently by using artificial neural network(ANN) technique. The quantification of such the seismic performance of the slope is not easy task due to the randomness and the uncertainty of the earthquake input and slope model. Under these circumstances, probabilistic seismic fragility analyses of slope have been carried out by several researchers, and a closed-form equation for slope seismic performance was proposed through a multiple linear regression analysis. However, a traditional statistical linear regression analysis has shown a limit that cannot accurately represent the nonlinearistic relationship between the slope of various conditions and seismic performance. In order to overcome these problems, in this study, we attempted to apply the ANN to generate prediction models of the seismic performance of the slope. The validity of the derived model was verified by comparing this with the conventional multi-linear and multi-nonlinear regression models. As a result, the models obtained through the ANN basically showed excellent performance in predicting the seismic performance of the slope, compared to the models obtained by the statistical regression analyses of the previous study.