• 월간 기계설비
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• no.9 s.206
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• pp.42-45
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• 2007

일반건설사들이 최근 시공 합리화를 통한 고부가가치 창출을 위해 건설현장의 전 과정을 데이터화한 정보시스템 개발 및 도입에 들어갔다. 건설사들이 선보인 현장관리시스템은 건설 프로젝트의 전 과정을 데이터화 및 공유하는 건설관리 정보화 시스템이다. 최근 들어 건설 산업의 전산화·정보화는 건설업무 진행 단계인 기획, 설계, 시공, 유지관리 절차에 따라 다양한 형태로 개발.활용되고 있다. 특히 시공단계에서 협력업체들 간의 다양한 정보공유로 불필요한 노동력 및 재정 낭비를 줄여 생산성 향상을 꾀하고 있다. 이번호에는 GS건설(주)의 현장관리시스템을 살펴본다.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.101-104
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• 2005

최근 들어 건설분야에서도 정보화를 통해 건설업무의 생산성 향상과 비용 절감을 위해 많은 시스템이 개발되고 있다. 이에 따라 건설정보시스템들에서 생성, 유통되는 정보자원이나 데이터가 다양하고 방대해지고 있다. 이를 위해 본 연구는 건설정보시스템들 간에 정보자원이나 데이터의 상호 연계성을 확보함으로써 언제, 어디서든지 필요한 정보자원이나 데이터을 추출하여 공유 및 재사용할 수 있는 메타데이터시스템 구축 방안을 마련하였고, 16종의 건설CALS 메타데이터를 개발하였다.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.422-426
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• 2006

Productivity is one of the very important index that measures efficiency of production activities in industry, enterprises and the building industry as well. None the less, the concept of construction productivity is not so clear that productivity management in the building industry have been performed by experience or intuition, productivity related data have not been analyzed through effective productivity management, because structured definition and classification of factors influencing construction productivity did not exist so that it has not been known what information explain each of them. In order to solve this problem, at first construction productivity and factors influencing construction productivity are defined and classified into three groups; (1)Project factors influencing construction productivity (2)Management factors influencing construction productivity (3)Activity factors influencing construction productivity. To find out relation between construction productivity and factors influencing construction productivity, a questionnaire survey for construction managers in the building industry has been conducted.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.827-831
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• 2007

For applying simulation to the construction process, much effort is needed to collect input data and to build the model including the characteristics of site. This study introduces the methodology to collect operation data of construction equipment and build the simulation model, then verifies the model with the operation data. In addition, this study identifies main factors to determine the cycle time of the muck hauling system and offers reasonable decision making data using the simulation based planning of construction equipment operation.

• Korean Journal of Construction Engineering and Management
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• v.20 no.2
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• pp.3-12
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• 2019

Despite the importance and function of productivity information, in the Korean construction industry, the method of collecting and analyzing productivity data has not been organized. Also, in most cases, productivity management is reliant on the experience and intuitions of field managers, and productivity data are rarely being utilized in planning and management. Accordingly, this study intends to develop a prediction model for interior finishes of apartment using deep learning techniques, so as to provide a foundation for analyzing the productivity impacting factors and predicting productivity. The result of the study, productivity prediction model for interior finishes of apartment using deep learning techniques, can be a basic module of apartment project management system by applying deep learning to reliable productivity data and developing as data is accumulated in the future. It can also be used in project engineering processes such as estimating work, calculating work days for process planning, and calculating input labor based on productivity data from similar projects in the past. Further, when productivity diverging from predicted productivity is discovered during construction, it is expected that it will be possible to analyze the cause(s) thereof and implement prompt response and preventive measures.

• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.3-12
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• 2022

In general construction project planning ratio of manpower and quantity of outputs produced, such as the construction estimate standard, is used as the criterion for labor productivity. This method is highly effective in construction projects with repetitive work, however, there is a limit to apply in large-scale projects with high complexity. This is because the influence of non-work time caused by various work interruption factors that act complexly on the productivity of the project is greater than the average labor productivity derived from the performance data of the project. Therefore, this study proposes a productivity measurement method that can evaluate the characteristics of construction works and the cause of non-working time. To this end, first, detailed work processes and their non-work factors for each work type are defined, and the Adv-FMR technique is developed for quantitatively measuring them. Next, based on the concept of obtainable productivity, methods for comparative productivity analysis by work type, evaluating non-work factors, and deriving productivity improvement methods are proposed. Finally, a case study is conducted to validate that the analysis results based on Adv-FMR data can support the decision-making of construction managers on productivity management.

• Korean Journal of Construction Engineering and Management
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• v.21 no.2
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• pp.15-21
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• 2020

The relationship between keywords, found in all productivity related papers published in the KSCE journal for last 15 years, were analyzed in order to reveal a research trend in the area using text mining and A-Priori algorithm. As the results, it is found that the word of 'productivity' is most closely related to the words of 'work' and 'labor'. Futhermore, the word is somewhat related to those of 'factor', 'model', simulation', and 'work time'. It is also revealed that, on the other hand, the words of 'machine' and 'equipment' have little relationships with the keyword. This research will be a great help for academia to understand a research trend in the area of construction productivity.

• The Journal of Bigdata
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• v.7 no.1
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• pp.99-111
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• 2022

A simulation technique can be used to analyze performance measures and support decision makings in manufacturing systems considering operational uncertainty and complexity. The simulation requires an input modeling procedure to reflect the target system's characteristics. However, data collection to build a simulation is quite limited when a target system includes manual productions with a lot of operational time such as construction equipment assembly lines. This study proposes a procedure for simulation input modeling using video data when it is difficult to collect enough input data to fit a probability distribution. We conducted a video-data analysis and specify input distributions for the simulation. Based on the proposed procedure, simulation experiments were conducted to evaluate key performance measures of the target system. We also expect that the proposed procedure may help simulation-based decision makings when obtaining input data for a simulation modeling is quite challenging.

• Korean Journal of Construction Engineering and Management
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• v.6 no.1 s.23
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• pp.89-98
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• 2005

Recently the construction industry in Korea is facing problems such as low productivity, contraction of the domestic construction market, growing competition, and so on. To enhance the competitiveness continuously through efficiency in this business environments, construction companies need to make efforts to measure and accumulate performance data based on the strategic factors. When analysing performance of construction projects, the unique characteristics of each project should be considered properly, by which the managers can identify current status of project in various perspectives. This study proposes the performance analysis system using the concepts of balanced scorecard and data warehouse technology. The suggested system provides the management with the flexibility in analyzing performance data by applying the pre-defined key performance indicators and the function of multi-dimensional analysis.

• Korean Journal of Construction Engineering and Management
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• v.5 no.6 s.22
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• pp.80-89
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• 2004

Among the various factors influencing construction productivity, weather conditions or elements become very important factors in planning and executing construction project. It is especially true in Korea where the weather changes dramatically through few seasons. In this study, relationship between construction productivity of the reinforced concrete structure we for the high-rise apartment buildings and 5 weather elements including temperature, humidity, day time, rainfall, and wind velocity have been analyzed The results trough regression analysis showed that weather elements explain $58.8\%$ of productivity in total and temperature and day time were more important factors among them.