• Journal of the Architectural Institute of Korea Structure & Construction
• /
• 제33권12호
• /
• pp.11-18
• /
• 2017

The safety inspection cost of the construction work was based on commercial facilities classified as a single building. Therefore, it is not possible to fully reflect the characteristics of the multi-building construction project such as apartment houses. Therefore, this study suggests a reasonable estimation model that can fully reflect the characteristics of the multi-building construction project. The safety inspection cost estimation model proposed two models such as construction cost ratio method and cost plus fixed fee method. And these models were simulated by the apartment construction work and compared with the current standard. As a result, the current construction cost ratio method has shown that the safety inspection cost tends to be overestimated as the construction size increases. Therefore, the proposed model has reflected characteristics of the multi-building construction project, so that it can reasonably estimate the safety inspection cost more than the current standard.

• Journal of Construction Engineering and Project Management
• /
• 제2권2호
• /
• pp.1-17
• /
• 2012

The automated construction machines have been recently developed to help solve the construction industry problems that significantly affect labour, productivity, quality, and profit. Despite the importance of performance analysis to commercialize the automated construction machines, previous studies have mainly concentrated on developing hardware and software of automated construction machines. This research now focuses on two objectives: (1) to propose an analysis model which can measure productivity, quality, and safety improvement rate of automated construction machines based on research and development (R&D); and (2) to develop a performance analysis system which will aid the evaluator in analysing the performance of automated construction machines. Finally, it is anticipated that the effective use of the performance analysis model and computerized system will ably develop the high-performance, automated construction machines and establish the marketing strategy to increase not only the commercial value but also the upkeep and development of construction machines.

• International conference on construction engineering and project management
• /
• The 6th International Conference on Construction Engineering and Project Management
• /
• pp.486-490
• /
• 2015

SWOT model was used to develop strategies for the Korean construction firms in entering the global construction market. Literature review, official statistics survey and other research methods were utilized in order to extract internal and external environmental factors of both the firm and local area. By extracting strength, weakness, opportunity and threat factors, a total of 12 strategies were produced: SO (Strengths-Opportunities), ST (Strengths-Threats), WT (Weaknesses-Threats), and WO (Weaknesses-Opportunities). The result of the study can be utilized as a basic data in developing a strategy for the Korean construction firms to penetrate into the global construction market.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• 한국건설관리학회 2002년도 학술대회지
• /
• pp.419-422
• /
• 2002

The features of modem construction industry can be summarized as specialization, complexity, and large-scale. Therefore, increasing uncertainty of construction project can not be effectively dealt with traditional method used for construction cost management. Cost overrun affects on successful execution of managing construction project in a negative way. Therefore, accurate estimation is a priori for effective cost management. First, this work analyzes the previous cost estimation model for the effective cost management. Then, a standard structure required for developing the cost estimation model for site development was presented. In addition, the cost estimation model which can be used in planning and design phases was introduced by analyzing real site development projects.

• Journal of the Korea Institute of Building Construction
• /
• 제11권1호
• /
• pp.91-99
• /
• 2011

Bayesian network is a form of probabilistic graphical model. It incorporates human reasoning to deal with sparse data availability and to determine the probabilities of uncertain cases. In this research, bayesian network is adopted to model the problem of construction project cost. General information, time, cost, and material, the four main factors dominating the characteristic of construction costs, are incorporated into the model. This research presents verify a model that were conducted to illustrate the functionality and application of a decision support system for predicting the costs. The Markov Chain Monte Carlo (MCMC) method is applied to estimate parameter distributions. Furthermore, it is shown that not all the parameters are normally distributed. In addition, cost estimates based on the Gibbs output is performed. It can enhance the decision the decision-making process.

• Korean Journal of Construction Engineering and Management
• /
• 제11권5호
• /
• pp.84-94
• /
• 2010

Partnering concept has been mentioned as an innovative arrangement that helps to reduce many of the disadvantages of the traditional arrangement. Partnering in construction has been widely applied in Vietnam from late 1990s. The application of the new has arrangement spread thanks to anecdotal proofs. This concept is quite new to Vietnamese practitioners. It is necessary to conduct study as a lesson-learn of the industry to encourage the partnering implementation. This paper attempts to develop a model, using discriminant analysis, which classifies the partnering in construction projects into success levels. Dedication, teamwork, sufficiency, and balance are the four significant components in discriminant model. The proposed model is helpful to practitioners in developing, adjusting and improving their strategy for partnering implementation.

• Journal of Construction Engineering and Project Management
• /
• 제3권2호
• /
• pp.21-34
• /
• 2013

Various risk factors affect construction projects. Due to the uncertainties created by risk factors, actual activity durations frequently deviate from the estimated durations in either favorable or adverse direction. For this reason, evaluation of schedule uncertainty is required to make decisions accurately when managing construction projects. In this regard, this paper presents a new computer simulation model - the Repetitive Schedule Risk Analysis Model (RSRAM) - to evaluate unit-based repetitive building project schedules under uncertainty when activity durations and risk factors are correlated. The proposed model utilizes Monte Carlo Simulation and a Critical Path Method based repetitive scheduling procedure. This new procedure concurrently provides the utilization of resources without interruption and the maintenance of network logic through successive units. Furthermore, it enables assigning variable production rates to the activities from one unit to another and any kind of relationship type with or without lag time. Details of the model are described and an example application is presented. The findings show that the model produces realistic results regarding the extent of uncertainty inherent in the schedule.

• Journal of the Korea Institute of Building Construction
• /
• 제13권2호
• /
• pp.159-168
• /
• 2013

Construction projects have become increasingly complex in recent years, resulting in substantial safety hazards and frequent fall accidents. In an attempt to prevent fall accidents, various safety management systems have been developed. These systems have mainly been evaluated qualitatively and subjectively by practitioners or supervisors, and there are few tools that can be used to quantitatively evaluate the performance of safety management systems. We propose an expertise-based safety performance evaluation model (EXSPEM), which integrates a fuzzy approach-based analytic hierarchy process and a regression approach. The proposed model uses S-shaped curves to represent the degree of contribution by subjective expertise and is verified by a genetic algorithm. To illustrate its practical application, EXSPEM was applied to evaluate the safety performance of a newly developed real-time mobile detector monitoring system. It is expected that this model will be a helpful tool for systematically evaluating the application of a robust safety control and management system in a complex construction environment.

• International conference on construction engineering and project management
• /
• The 5th International Conference on Construction Engineering and Project Management
• /
• pp.226-230
• /
• 2013

In the tall building construction, the slab formwork largely impacts on construction cost. Because productivity of a slab formwork is influenced by a number of and the efficiency of equipment, using the equipment-based construction method, an appropriate equipment input planning is crucial for the productivity. Meanwhile, the general equipment input planning is conducted by intuition based on experience due to the lack of equipment productivity data. Thus, this study develop a simulation model to analyze table formwork productivity and to propose an optimum equipment input plan that reflects the construction process, based on the full consideration of the economic factors. This study developed a simulation model by using CYCLONE and the data for the model was collected by measuring the duration of each unit activity in the tall building where table forms were applied. It is expected that a simulation model helps users to make better decision on the equipment input planning of slab formwork.

• Journal of the Korea Institute of Building Construction
• /
• 제17권3호
• /
• pp.295-303
• /
• 2017

Over the past 7 years, the number of victims of construction disasters has been gradually increasing. Compared with projects in other industries, construction projects are highly exposed to safety risks. For this reason, the research methods of predicting and managing the risk of construction disasters are urgently needed that can be applied to a construction site. This study aims to propose a prediction model for a construction disaster using the decision tree technique. The developed the model is reviewed the applicability by evaluating its accuracy based on disaster data. The top three of the prediction values obtained from the proposed model were enumerated, and then the cumulative accuracy were also calculated. The prediction accuracy was 40 percent for the first value, but the cumulative accuracy was 80 percent. Thus, as more disaster data was accumulated, the cumulative accuracy appeared to be higher. If utilized in construction sites, the model proposed in this study would contribute to a reduction in the rate of construction disasters.