• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.661-670
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• 2006

The utilization of simulation has been limited in planning construction process because it is difficult to collect data and build a model using simulation method. This study collects construction operation data and analyzes the characteristics of its distribution. Through the statistical analysis on the empirical data, this study identifies Beta distribution functions is one of the most proper in duplicating the characteristics of construction equipment operation data into a computer simulation. The information obtained in this study can support preparing input data for another simulation.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.686-693
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• 2022

Construction is a collaborative endeavor. The complexity in delivering construction projects successfully is impacted by the effective collaboration needs of a multitude of stakeholders throughout the project life-cycle. Technologies such as Building Information Modelling and relational project delivery approaches such as Alliancing and Integrated Project Delivery have developed to address this conundrum. However, with the onset of the pandemic, the digital economy has surged world-wide and advances in technology such as in the areas of machine learning (ML) and Artificial Intelligence (AI) have grown deep roots across specializations and domains to the point of matching its capabilities to the human mind. Several recent studies have both explored the role of AI in the construction process and highlighted its benefits. In contrast, literature in the organization studies field has highlighted the fear that tasks currently done by humans will be done by AI in future. Motivated by these insights and with the understanding that construction is a labour intensive sector where knowledge is both fragmented and predominantly tacit in nature, this paper explores the integration of AI in construction processes across project phases from planning, scheduling, execution and maintenance operations using literary evidence and experiential insights. The findings show that AI can complement human skills rather than provide a substitute for them. This preliminary study is expected to be a stepping stone for further research and implementation in practice.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.82-86
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• 2015

Construction delay is a common problem worldwide, which is considered as one of the main reasons for project failure. Bangladesh construction industry is no exception. This study investigated the main causes of delay in large building construction projects in Bangladesh. A questionnaire survey was conducted to determine the causes of delay from owners, consultants, and contractors of large building construction projects. About 70 respondents participated in the survey. Using the importance index analysis, the study identified 10 most important causes of delay from a list of 30 different causes. Ten most important causes were: (1) lack of experienced construction manager, (2) lowest bidder selection, (3) funding shortage by owner, (4) lack of proper management, (5) improper planning and scheduling, (6) lack of skilled workers, (7) site constraints, (8) contractors' cash flow problems during construction, (9) escalation of resources price, and (10) contractors' excessive workload. Furthermore, Kruskal-Wallis test indicates that there is no significant variation exists among the three group of respondents, ie owners, consultants and contractors.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.287-293
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• 2013

The annual expenditure on diesel oil and heavy oil in the construction sector is the second largest among all industrial sectors. According to the greenhouse reduction scheme of Korean Government, construction sector targeted 7.1% reduction by 2020. Although this target is not higher than other industrial sectors, it is not easy to achieve the reduction target without radical advance in technology, which cannot be expected to happen soon, considering the conservative characteristics of construction industry. Most researches on environmental issues focus on the issues related to energy saving matters during material production stage or maintenance stage, such as heating and insulation, and few deal with the issues directly related to the energy use in the construction sites. This research regards the operation of equipment for the on-site construction processes as a system and attempts to model the energy use processes related to the activities in construction sites, and provides simulation results of earth excavation and hauling processes. The result of this research is expected to aid construction planners estimating the time-based patterns of energy use and assessing greenhouse gas emission and to help selecting more energy efficient alternatives at the planning stage.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.223-224
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• 2023

Optimal fleet management in the planning stage is one of the most critical activities that guarantee successful construction projects. In South Korea, the construction standard production rate database (CSPRD) is normally employed. However, when it comes to a trade-off problem that involves decision-making on optimal sets of equipment to perform a certain task, the method will require the planners' in-depth knowledge and experience regarding the target process and a time consuming estimation of the performance of every possible scenario must be conducted for the deduction of the optimal fleet management. On this account, this research paper proposes a lightweight method of using mixed integer nonlinear programming (MINLP) in multi-objective problems based on CSPRD-based mathematical equations to assist planners in the preplanning stage of choosing the optimal sets of types and size machinery to efficiently arrange the construction scheduling and budgeting.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.199-204
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• 2023

Periodic assessment of reservoir capacity is essential for better water resources management and planning for the future water use. Reservoirs and water storage structures raised on the rivers are subjected to sedimentation and he sedimentation is caused by deposition of eroded sediment particles carried by the streams. Knowledge of reservoir sedimentation is important to estimate avaliable storage capacity for optimum reservoir operation and scheduling water release. In recent years, remote sensing and GIS techniques have emerged as an important tool in carrying out reservoir capacity analysis and water management. The reduction in storage capacity as compared to the original capacity at the time of reservoir impounding is indicative of sediment deposition. In this study, the application of GIS and remote sensing techniques were applied to assess the sediment deposition, losses in the reservoir storage and the revised cumulative capacity. Satellite images covering Pyodongdong reservoir were analyzed using Erdas Imagine and ArcGIS softwares.Cumulative capacities at different levels were also calculated and we estimated that the revised live storage was 84.2Mft3 in 2021 and 64.3Mft3 in 2022 while the original capacity was 22.8 and 53.6Mft3 in 2021 and 2022.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.3
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• pp.1-13
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• 2020

The management of agricultural water can be divided into management of agricultural infrastructure and operation to determine the timing and quantity of water supply. The target of water management is classified as water-supply facilities, such as reservoirs, irrigation water supply, sluice gate control, and farmland. In the case of agricultural drought, there is a need for water supply capacity in reservoirs and for drought assessment in paddy fields that receive water from reservoirs. Therefore, it is necessary to analyze the water supply amount from intake capacity to irrigation canal network. The analysis of the irrigation canal network should be considered for efficient operation and planning concerning optimized irrigation and water allocation. In this study, we applied a hydraulic analysis model for agricultural irrigation networks by adding the functions of irrigation canal network analysis using the SWMM (Storm Water Management Model) module and actual irrigation water supply log data from May to August during 2015-2019 years in Sinsong reservoir. The irrigation satisfaction of ponding depth in paddy fields was analyzed through the ratio of the number of days the target ponding depth was reached for each fields. This hydraulic model can assist with accurate irrigation scheduling based on its simulation results. The results of evaluating the irrigation efficiency of water supply can be used for efficient water distribution and management during the drought events.

• Journal of Korean Society of Forest Science
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• v.82 no.3
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• pp.292-304
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• 1993

This research developed a forest-level harvest scheduling model using linear programming (LP). The formulations of the LP model include timber production schemes with constraints of nondecling yield forest conversion strategies, the minimum timber supply, levels and the maximum cut acrages. The model is able to generate both Model I and Model II types of input matrix in MPS format. In this paper, use of LP in building the framework of the strategic forest planning model was justified by comparing the algorithmic characteristics of LP with those of Gentan probability and binary search approaches through literature reviews. In order to demonstrate the field applicability of the model proposed. (1) the harvest scheduling problem for about 11,000-hectare case study area (Mt. Baekun area in Southern Experimental Forest of Seoul National University) was formulated and soloed and (2) the effects of the change in task regulatory timber production constraints or. optimal harvesting schedules here investigated.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.89-97
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• 2016

This paper addresses the problem of the construction planning of artillery positions, for which we present an optimization model and propose a heuristic algorithm to solve problems of practical size. The artillery position construction plan includes the assignment of engineers to support the artillery and the schedule of the support team construction sequence. Currently, in the army, managers construct the plan based on their experience. We formulate the problem as a mixed integer program and present a heuristic that utilizes the decomposition of the mixed integer model. We tested the efficacy of the proposed algorithm by conducting computational experiments on both small-size test problems and large-size practical problems. The average optimality gap in the small-size test problem was 6.44% in our experiments. Also, the average computation time to solve the large-size practical problems consisting of more than 200 artillery positions was 79.8 seconds on a personal computer. The result of our computational experiments shows that the proposed approach is a viable option to consider for practical use.

• Korean Journal of Construction Engineering and Management
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• v.1 no.2 s.2
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• pp.89-97
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• 2000

This research has been Initiated to provide an effective management tool for budget control of the public projects using EVMS. Barriers to implementing the tool for the domestic public projects are identified : no PMB (Performance Measurement Baseline) for budget control, management by BOQ(bill of quantity), no systematic planning and control. To eliminate these barriers, an integrated cost and schedule management process model using EVMS is proposed. This model is composed of six sub processes : organizing, scheduling, budget allocating, establishing PMB, managerial analysis, change incorporation.