• Korean Journal of Construction Engineering and Management
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• v.7 no.2 s.30
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• pp.127-137
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• 2006

Productivity is important to evaluate an efficiency of performed work and organization in construction industry. The productivity should be defined as activity level rather than macro level in order to effectively use productivity data and manage a project. The primary objective of this study is to develop a construction productivity management system using data warehouse, OLAP and data mining technologies which enables to easily accumulate the construction productivity data and perform multi layer analysis. Finally, it is anticipated that the effective use of the developed system would be able to measure the result of project and make a plan of the similar project with reliability.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.813-818
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• 2007

Construction productivity is a key factor for efficiency evaluation of construction work process, project performance measurement, and basic data of work plan in construction industry. However, although construction productivity is important in construction industry, gathering methodology and analyzing methodology of productivity data are not well-organized therefore productivity data is not utilized in the construction industry The purpose of this study is to develop productivity prediction system using data mining technology based on activities and to suggest frameworks about productivity data collection, accumulation.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.548-553
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• 2006

Activity-based productivity data can be used as an significant reference in many areas of project management such as performance evaluation and project planning. However, the existence of various factors influencing construction productivity makes it difficult to collect and analyze the productivity data. In the most of the domestic construction sites, there is no systematic method to collect and analyze the productivity data along with information on influencing factors; it is common to heavily rely on experience and intuition of field managers when dealing with construction productivity data. Therefore it is necessary to develop a management system for collecting and utilizing the productivity data as well as the factors influencing construction productivity. The main objective of this research is to define the construction productivity and its influencing factors at the activity level. In addition, methodologies on how to analyze the productivity data and to estimate productivity of future projects are proposed.

• Korean Journal of Construction Engineering and Management
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• v.9 no.5
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• pp.86-94
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• 2008

Productivity is one of key management indexes for evaluating soundness of a manufacturing organization and its efficiency. In many aspects of productivity management in the construction industry, however, intuition of an experienced field manager still plays a greater role while productivity data is not utilized efficiently for the construction management purposes, because the collection and analysis of the productivity-related information are not systematic. Lack of systematic method in collecting and analyzing the productivity data results in such problems. The existing WBS should therefore be improved to solve them. The authors developed a new WBS for productivity data collection and analysis by following the research direction that was determined by literature reviews, overseas cases, and interviews with field engineers. The new breakdown structure was then evaluated for its feasibility as a productivity analysis framework. It is expected that the productivity data collected by the WBS will be used for OLAP and mining for future productivity forecast.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.442-445
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• 2002

Construction delay claim occurs more often than any other claim. Delay claim impacts adversely the company's existence as well as the project's monetary problem. Because the calculation of the delay is not quantitative, owing not to have enough evidence, it is hard to solve evenly the delay claim. So, it is need to cumulate structurely the construction data or evidence during the construction. This study considers the established study about construction delay claim database and the problems and then presents the relation method between phase schedule and database. Finally, this study established the productivity claim database modeling for construction project through conceptual database modeling and logical database modeling based on information needed to make construction productivity database. So. the purpose of the study is to establish the datamodel for productivity management of construction project for calculating the delay days considering the lost productivity.

• Korean Journal of Construction Engineering and Management
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• v.4 no.4 s.16
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• pp.164-172
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• 2003

생산성은 프로젝트를 관리하는데 있어서 효율성을 측정하는 중요한 지표이다 또한 건설 생산성은 비용 및 일정과 연관성이 있을 뿐만 아니라 프로젝트의 성공 여부와도 관련이 크다. 프로젝트에서 생산성의 중요성에도 불구하고 국내에서의 생산성 관련 연구는 생산성에 대한 기본 개념 및 원칙에 관한 기초적인 연구 없이 정량적인 연구에 집중되어 있으며, 관련 데이터 수도 적은 실정이다. 국내 건설 공사의 생산성을 향상시키기 위해서는 생산성 관리의 정량적친 요인뿐만 아니라, 정성적인 요인까지 관리해야 하며, 저하요인에 따른 체계적이고 세부적인 프로세스 및 기법이 제시되어야 한다 이에 국내 건설 공사의 생산성 관리에 린 건설을 도입하고자 한다. 본 연구에서는 국내 생산성 저하요인과 린 건설에서의 Waste 요인과의 상관관계 분석을 통해 국내 건설 공사 현장에서의 Waste 주요 의미를 살펴보고 두 요인간의 상호 관련성을 파악하여, 린 건설의 프로세스 및 기법을 국내 건설 공사 현장에 적용하기 위한 이론적인 근거를 제공하고자 한다.

• Journal of the Korea Institute of Building Construction
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• v.11 no.2
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• pp.100-107
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• 2011

As construction duration significantly influences the performance and the success of construction projects, it is necessary to appropriately manage the impact factors affecting construction duration. Recently, interest in the construction industry has been rising due to the recent change in the construction legal system, and the competition among the construction companies on construction time. However, the impact factors are extremely diverse. The existing productivity data on impact factors is not sufficient to properly identify the impact factor and measure the productivity from various perspectives, such as subcontractor, time, crew, work and so on. In this respect, a multidimensional analysis by a data warehouse is very helpful in order to view the manner in which productivity is affected by impact factors from various perspectives. Therefore, this research proposes a method that effectively takes the diverse productivity data of impact factors, and generates a multidimensional analysis. Decision tree analysis, a data mining technique, is also applied in this research in order to supply construction managers with appropriate productivity data on impact factors during the construction management process.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.95-100
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• 2004

본 논문은 도로 건설 공사 프로젝트들의 전 공정에 걸쳐 수행되는 모든 작업들을 대상으로 총 프로젝트 생산성 (Total Project Productivity)을 측정하고 분석하기 위한 방법을 소개한다. 측정 방법의 주안점은 복합적으로 병행되는 작업들의 생산량을 통합하여, 프로젝트 전체에 대한 포괄적인 생산성 값들을 구하는 방법을 개발하는데 두고 있다. 이 방법을 통해 Florida Department of Transportation (FDOT)로부터 발주된 세 개의 실제 고속도로 건설 공사 프로젝트들로부터 수천 개의 총 프로젝트 생산성 데이터 값들이 얻어졌으며. 이를 바탕으로 프로젝트 생산성을 분석하기 위한 방법의 타당성 검증이 이루어졌다. 그 결과로, 프로젝트 레벨에서의 총 생산성은 건설 작업들에 관한 현장 자료를 바탕으로 측정과 분석이 이루어질 수 있음이 입증되었다.

• Korean Journal of Construction Engineering and Management
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• v.24 no.3
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• pp.3-11
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• 2023

This research examines the need for a quantitative and objective method of calculating baseline productivity in the construction industry, which is known for its high volatility in performance and productivity. The existing literature's baseline productivity calculation methods rely heavily on subjective criteria, limiting their effectiveness. Additionally, data collection methods such as the "Five-minute Rating" are costly and time-consuming, making it challenging to collect detailed data at construction sites. To address these issues, this study proposes an objective baseline calculation method using unimpacted productivity BP, a work check sheet to systematically record detailed data, and a data collection and utilization process that minimizes cost and time requirements. This paper also suggests using unimpacted productivity BP and comparative analysis to address the objectivity and reliability issues of existing baseline productivity calculation methods.

• 월간 기계설비
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• no.2 s.211
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• pp.56-60
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• 2008

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 롯데건설(주)의 현장관리시스템을 살펴본다.