• Proceedings of the KSR Conference
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• 2009.05a
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• pp.1062-1068
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• 2009

Urban construction has numerous difficulties due to ground weakness and various complaints from third party, so it is not economically efficient and constructability is not favorable. Therefore, underground, which has good ground conditions, was used for construction field and facilities such as stations, and they are scaled up to enhance accommodation of facility limitation and function of stations. Large section tunnel station construction has numerous risk factors such as work boundary of excavation equipment, a relaxation of stress concentration, a safety plan of tunnel stability, and so on. Therefore, by using large section tunnel station stability analysis considering construction step, we expect to analyze the latent problem during construction, and to stabilize a future project plan of a large section structure design by using an auxiliary method and a support design.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.823-830
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• 2022

The risk of project execution increases due to the enlargement and complexity of Engineering, Procurement, and Construction (EPC) plant projects. In the fourth industrial revolution era, there is an increasing need to utilize a large amount of data generated during project execution. The design is a key element for the success of the EPC plant project. Although the design cost is about 5% of the total EPC project cost, it is a critical process that affects the entire subsequent process, such as construction, installation, and operation & maintenance (O&M). This study aims to develop a system using machine-learning (ML) techniques to predict risks and support decision-making based on big data generated in an EPC project's design and construction stages. As a result, three main modules were developed: (M1) the design cost estimation module, (M2) the design error check module, and (M3) the change order forecasting module. M1 estimated design cost based on project data such as contract amount, construction period, total design cost, and man-hour (M/H). M2 and M3 are applications for predicting the severity of schedule delay and cost over-run due to design errors and change orders through unstructured text data extracted from engineering documents. A validation test was performed through a case study to verify the model applied to each module. It is expected to improve the risk response capability of EPC contractors in the design and construction stage through this study.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.379-380
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• 2023

The Post-Construction Evaluation and Management System has been operated over the past 20 years not only to analyze the performance of large-scale construction projects, and but also to provide useful reference data for future similar projects. Although the Post-Construction Evaluation and Management Center has been legally designated and operated since 2020, various problems have been occurring in the operation of the system. Accordingly, this study proposes strategies for facilitating Post-Construction Evaluation and Management System in terms of the following three aspects: (1) improving the implementation rate of post-construction evaluation; (2) improving the information management system related to post-construction evaluation; (3) improving the utilization of post-construction evaluation outcomes. Based on the results of this study, a specific action plan will be prepared, which is expected to contribute to the efficiency of construction project performance management in the future.

• Korean Journal of Construction Engineering and Management
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• v.19 no.1
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• pp.43-53
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• 2018

Modular construction can improve construction quality and accuracy through manufacturing process, and it allow massive production and cost savings by repeatedly producing the same unit. In particular, it is possible to reduce the time because the on-site work and the manufacturing process can be carried out at simultaneously. However, according to the modular construction project survey report, there is no significant difference regarding the average construction period between modular construction and conventional construction. This is due to schedule delay problems that occur during construction phase. Therefore, it is necessary to select alternatives to prevent schedule delay during on-site construction progressing. Especially, in case of large-scale modular construction project, on-site module assembly and manufacturing process are performed concurrently. Hence, identification of alternatives should be done at the co-occurrence by taking both manufacturing and on-site work process in to account. In this research, the management factors of large-scale modular construction project were identified through the IDEF0 modeling, and the quantity management model for manufacturing and assembly is developed. This will reduce the schedule delay problem that occurs in the progression on-site work of a large scale modular construction.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.1155-1162
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• 2004

This research proposes a new risk analysis method in order to guarantee successful performance of construction projects. The proposed risk analysis methods consists of four phases. First step, AHP model can help contractors decide whether or not they bid for a project by analysing risks involved in the project. Second step, the influence diagraming, decision tree and Monte Carlo simulation are used as tools to analyze and evaluate project risks quantitatively. Third step, Monte Carlo simulation is used to assess risk for groups of activities with probabilistic branching and calendars. Finally, Fuzzy theory suggests a risk management method for construction projects, which is using subjective knowledge of an expert and linguistic value, to analyze and quantify risk. The result of study is expected to improve the accuracy of risk analysis because three factors, such as probability, impact and exposure, for estimating membership function are introduced to quantify each risk factor. Consequently, it will help contractors identify risk elements in their projects and quantify the impact of risk on project time and cost.

• Korean Journal of Computational Design and Engineering
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• v.17 no.4
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• pp.225-233
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• 2012

A comprehensive research effort in order to develop and disseminate modernized Korean housing (Hanok) has recently been initiated by Korean government. This large scale research project encompasses a wide spectrum of housing development including public policy, architectural plans, modules, construction materials and methods, prefabricated assemblies, automated production, construction management, and advanced information systems. For the purpose of integrating and automating the whole processes from an industry perspective, it is of great importance to develop a standard classification system and project numbering system (PNS) for the modernized Korean housing. This paper focuses on the standard classification systems and PNS for cost and schedule control. The distinct characteristics and managerial requirements were explored and embedded into the proposed classifications for modernized Hanok.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.717-724
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• 2009

Most recent programs in and out of the country are related to urban renewal projects. Contemporary project management information systems have been developed was to manage single or multiple projects focusing on their construction phase, and those have limitations to apply to large-scale complicated mega projects. So, this study explain the core concept of decision support modules for iPMIS (Intelligent Program Management Information System) and its major functions to support project owner and participants by introducing ontology in the web environment. This study confined the scope of research to the planning phase of urban environment improvement projects. Ontological logic structure and relation about planning works is essential parts and three functions to implement decision support module are developed.

• Journal of KIBIM
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• v.3 no.2
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• pp.19-27
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• 2013

The application of the BIM for the KEPCO' new headquarters in Naju involved alternative approaches and accompanied many trials-and-errors as the project adopted new targets and purposes that were not used in Korea before. In particular, for a large BIM-based project, clearly defining the BIM-including the objective, scope and the outcome-is critical for a project owner. For a successful implementation, project owners should improve the utilization of the BIM. Against this background, this research examines the case of the BIM application for the KEPCO' new headquarters in Naju, identifies its effects and problems, and proposes how to improve application of the BIM for public projects. The improvement in the BIM application can be divided into several stages: project order, design development, construction, and post-construction maintenance. In the initial stage, it is important to fully discuss the project planning among participants, and clarify the goal, scope, expected outcomes and role of the BIM. In the design stage, the level of detail (LOD) for the 3D model should be defined in consideration of information use in the stages of estimation and construction. In the construction stage, the scope of project that is managed based on the processing and use of the BIM data should be clearly given and understood. After construction is complete, measures should be sought to use the BIM for maintenance, and corresponding requirements and outcomes should be provided. The analysis is expected to provide basic data for successful implementation of BIM-based public projects, by assisting project owners and involved parties in enhancing work in different stages of a project.

• Korean Journal of Construction Engineering and Management
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• v.5 no.3 s.19
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• pp.153-165
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• 2004

Most engineering tasks require collaboration between many users in major hospital construction projects that have many reconstructions. Loss and change orders occurred in factors such as information exchange, misunderstandings, advanced technology in hospital projects. Moreover, changes in context, costs, requirements, deadlines, etc. require negotiation of issues that may modify important project characteristics. The objective of this paper is to reduce reconstruction for the pre-construction process of hospital projects, reconstruction factors were analyzed in recent hospital construction project the system was established in order to solve reconstruction factors, and this system was validated through applying to the real project. Therefore it is a major challenge to make high level of communication and to have mutual understanding.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.58-65
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• 2011

Construction Productivity is one of the most important elements in construction management. It is used in construction process scheduling and cost management, which are significant sector in construction management. It is important to make appropriate schedule and monitor how works are done within schedule. But construction project contains uncertainty and inexactitude, modifying construction schedule is being an issue to manage construction works well. Even though prediction and monitoring of productivity can be principal activity, it is hard to predict productivity with manager's experience and a standard of estimate. A large number of factors influencing productivity, such as drawing, construction method, weather, labor, material, equipment, etc. But current calculation of productivity depends on empirical probability, not consider difference of each influencing factor. In this research, the aim is to present a productivity predicting regression model of form work, which includes effectiveness of influences factors. 5 variables existed inside form work are selected by interview and site research based on literature review of existed various productivity influencing factors. The effectiveness and correlation of productivity influencing factors are analyzed by statistical approach, and it is used to make productivity regression model. The finding of this research will improves monitoring and controlling of project schedule in construction phase.