• International conference on construction engineering and project management
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• 2009.05a
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• pp.847-855
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• 2009

While many studies on feasibility analysis for housing projects have been released, the main focus was on economic feasibility and factors related to developers were not clearly identified enough to be used in practice. In order to establish a feasibility analysis model for apartment development projects requested by developers in Korea, 31 driving factors behind projects' success were identified under seven different categories. Criterions of the each factor were also developed, and weight of each factor was assigned by applying the Analytical Hierarchy Process(AHP). Finally, based on the Monte Carlo simulation, the feasibility analysis model was established, providing probability distribution of project's grade. The model was applied to 12 housing projects to verify its reliability, and found that the model properly filtered projects that are unlikely to be profitable, indicating reasonable reliability of the model. The model can be a useful tool for contractors, especially with less experience in analyzing project development feasibility.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.417-424
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• 2009

For a construction project to progress smoothly, effective cost estimation is vital, particularly in the conceptual and schematic design stages. In these early phases, despite the fact that initial estimates are highly sensitive to changes in project scope, owners require accurate forecasts which reflect their supplying information. Thus, cost estimators need effective estimation strategies. Practically, parametric cost estimates are the most commonly used method in these initial phases, which utilizes historical cost data (Karshenas 1984, Kirkham 2007). Hence, compilation of historical data regarding appropriate cost variance governing parameters is a prime requirement. However, precedent practice of data mining (data preprocessing) for denoising internal errors or abnormal values is needed before compilation. As an effort to deal with this issue, this research proposed a statistical methodology for data preprocessing and verified that data preprocessing has a positive impact on the enhancement of estimate accuracy and stability. Moreover, Statistically Preprocessed data Based Parametric (SPBP) cost models are developed based on multiple regression equations and verified their effectiveness compared with conventional cost models.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.275-276
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• 2023

In order to prevent disaster risks caused by building aging in advance, the prevailing opinion is that it is urgent to actively improve systems such as mandatory safety inspections, and to calculate risks and develop safety management systems due to building aging. The need for systematic risk management continues to be emphasized in the process of safety inspection and repair of old buildings, but the risk management and safety management techniques of each construction entity have not been established in practice. Accordingly, this study aims to analyze the vulnerability factors of aging buildings and provide basic data on the development of a risk rating calculation model for old buildings and the efficiency of safety management systems in the future.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.23-30
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• 2011

The people in the AEC industry have acknowledged and long struggled to solve the critical low productivity issue of the entire construction industry. Integrated Project Delivery has been suggested as a solution to this problem and to take this into practice many countries have come up with BIM guidelines. In order to make this a success, BIM design process and LOD must be dealt in advance. The following research has selected 3 out of 16 guidelines that specifically describes BIM process and LOD, and intends to fully acknowledge its concept by comparing the approach and definition of LOD in the BIM Design Process.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.328-335
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• 2022

With the advance of robot capabilities and functionalities, construction robots assisting construction workers have been increasingly deployed on construction sites to improve safety, efficiency and productivity. For close-proximity human-robot collaboration in construction sites, robots need to be aware of the context, especially construction worker's behavior, in real-time to avoid collision with workers. To recognize human behavior, most previous studies obtained 3D human poses using a single camera or an RGB-depth (RGB-D) camera. However, single-camera detection has limitations such as occlusions, detection failure, and sensor malfunction, and an RGB-D camera may suffer from interference from lighting conditions and surface material. To address these issues, this study proposes a novel method of 3D human pose estimation by extracting 2D location of each joint from multiple images captured at the same time from different viewpoints, fusing each joint's 2D locations, and estimating the 3D joint location. For higher accuracy, the probabilistic representation is used to extract the 2D location of the joints, considering each joint location extracted from images as a noisy partial observation. Then, this study estimates the 3D human pose by fusing the probabilistic 2D joint locations to maximize the likelihood. The proposed method was evaluated in both simulation and laboratory settings, and the results demonstrated the accuracy of estimation and the feasibility in practice. This study contributes to ensuring human safety in close-proximity human-robot collaboration by providing a novel method of 3D human pose estimation.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.585-594
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• 2024

In recent years, the construction industry has rapidly adopted offsite-manufacturing and distributed construction methods. This change brings a variety of challenges requiring innovative solutions, such as the utilization of AI-driven and generative design. Numerous studies have explored the concept of multi-objective generative design with genetic algorithms in construction. However, this paper highlights the challenges and proposes a solution for combining generative design with distributed construction to address the need for agility in design. To achieve this goal, the research delves into the development of a multi-objective generative design optimization using a weighted genetic algorithm based on simulated annealing. The specific design case adopted is an educational complex. The proposed process strives for scalable economic viability, environmental comfort, and operational efficiency by optimizing modular configurations of architectural spaces, facilitating affordable, scalable, and optimized construction. Rhino-Grasshopper and Galapagos design tools are used to create a virtual environment capable of generating architectural configurations within defined boundaries. Optimization factors include adherence to urban regulations, acoustic comfort, and sunlight exposure. A normalized scoring approach is also presented to prioritize design preferences, enabling systematic and data-driven design decision-making. Building Information Modeling (BIM) tools are also used to transform the optimization results into tangible architectural elements and visualize the outcome. The resulting process contributes both to practice and academia. Practitioners in AEC industry could gain benefit through adopting and adapting its features with the unique characteristics of various construction projects while educators and future researchers can modify and enhance this process based on new requirements.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.11a
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• pp.227-228
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• 2012

In contemporary architectural practice, flat sections and plan drawings are no longer a primary means of representation and communication with participants. A typical building design has an ornamental exterior wall system and a roof system that should have water-proof quality and drainage function. By comparison, distinction between exterior wall and roof are unclear in freeform buildings, and they are integrated into a concept of a building envelope. This study is to propose 3D coordinate control technology for freeform structure by CNC curved tube method in order to develop a BIM-based envelope design and construction method for freeform building. Because a much wider freeform building construction can be achieved with correct 3D data and easy-to-implement in construction field, the proposed 3D coordinate control technology is highly recommended for practical use instead of the conventional CAD system.

• Journal of The Korean Digital Architecture Interior Association
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• v.10 no.3
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• pp.87-95
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• 2010

The CM(Construction Manager) of D-university has been seeking the advice of my BIM-team to adopt CM(Construction Management) and BIM best practices to improve project delivery results, and has authored best practice reports for spatial validation, BIM, 3D, 4D and 5D performance. Building Information Modeling(BIM) Process, Integration, and Adoption looks at BIM implementation from a company and project level laying out a process for companies to use BIM. Following this studies, participants will be able to: 1. BIM participants has been creating a BIM process diagram for a project, and has been evaluating and selecting process options for a specific BIM project. 2. BIM participants has been describing the roles and responsibilities of participants in the BIM process, and has been communicating the BIM process to management, colleagues, and project stakeholders. 3. BIM participants has been identified consistent factors influencing BIM return on investment at the project level and the company level, and has been outlining a process for BIM adoption on the project level and company level.

• Journal of the Korea Institute of Building Construction
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• v.13 no.4
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• pp.372-381
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• 2013

In the construction industry, a great deal of research has been focused on productivity improvement because a minor change in labor productivity can often make the difference between a profit and a loss. This study shows how productivity measurement methods can be applied in practice, step by step, to analyze and identify potential problems both in productivity and methods performance for masonry work. A work sampling technique was conducted to determine the nature and extent of an observable activity as an aid to measuring overall performance. Also, a method productivity delay model was used to identify non-productivity in individual cycle times. From the work sampling technique, it was found that the masonry crew had a Labor Utilization Factor of 47.1%, and from the videotape analysis, it was found that the material and dumpster location need to be adjusted to reduce the travelling distance. We have found that efforts to improve the productivity of masonry work should be focused almost exclusively on machine and labor delays, based on the result from the method productivity delay model.

• Korean Journal of Construction Engineering and Management
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• v.5 no.5 s.21
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• pp.151-162
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• 2004

Current methods for construction site modeling employ large, expensive laser range scanners that produce dense range point clouds of a scene from different perspectives. Days of skilled interpretation and of automatic segmentation may be required to convert the clouds to a finished CAD model. The dynamic nature of the construction environment requires that a real-time local area modeling system be capable of handling a rapidly changing and uncertain work environment. However, in practice, large, simple, and reasonably accurate embodying volumes are adequate feedback to an operator who, for instance, is attempting to place materials in the midst of obstacles with an occluded view. For real-time obstacle avoidance and automated equipment control functions, such volumes also facilitate computational tractability. In this research, a human operator's ability to quickly evaluate and associate objects in a scene is exploited. The operator directs a laser range finder mounted on a pan and tilt unit to collect range points on objects throughout the workspace. These groups of points form sparse range point clouds. These sparse clouds are then used to create geometric primitives for visualization and modeling purposes. Experimental results indicate that these models can be created rapidly and with sufficient accuracy for automated obstacle avoidance and equipment control functions.