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A Study on the Task Variation and Social Network Analysis in the Construction Process

시공 프로세스에서 발생하는 공사변동 요인 및 네트워크 분석에 관한 연구

  • Park, Yoona (Department of Architectural Engineering, Hanyang University) ;
  • Lee, Dongdeok (Department of Construction Management, Hanyang University) ;
  • Kim, Jaejun (Department of Architectural Engineering, Hanyang University)
  • Received : 2018.09.27
  • Accepted : 2018.10.31
  • Published : 2019.01.31

Abstract

A construction project is a complex process consisting of interdependent tasks. If one task has variation, other tasks will be affected additionally and it is difficult to reach consensus on task variation due to the characteristics of the construction site that is going on quickly and complicatedly. Therefore, this study identified the root cause of task variation in construction process. Adjacent matrix was created with the tasks corresponding to major causes of variation, and the network analysis was performed. The results of social network analysis in the construction process can stabilize the work flow in the complex process and improve the reliability of the process plan and the project performance.

하나의 건설 프로젝트에는 다양한 작업들이 상호의존적으로 진행되어 복잡한 프로세스를 이룬다. 한 작업에서 공사변동이 발생하면 추가적으로 다른 작업들도 영향을 받게 되며 신속하게 진행되는 건설현장 특성상 매번 변동에 대한 합의를 도출하기는 매우 어렵다. 이에 본 연구에서는 시공 과정에 발생하는 공사변동에 대한 근본원인을 파악하고 주요 공사변동요인에 해당하는 작업들에 대하여 인접행렬을 구축하여 네트워크 분석을 실시하였다. 이를 통해 작업들 간 관계론적 특성과 구조적 위치를 파악하였다. 이러한 시공 프로세스에서의 작업 네트워크 분석을 통해 복잡한 시공 과정에서의 작업흐름을 안정화 시키고자 하며 공정 계획의 신뢰성과 프로젝트 성과를 향상시키고자 한다.

Keywords

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Fig. 1. Starting time and task duration on risk assessment matrix

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Fig. 2. Trades associated with the top three causes of variation

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Fig. 3. Project 1 network visualization

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Fig. 4. Results of degree centrality for all project

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Fig. 5. Results of eigenvector centrality to identify key trades

Table 1. Case study

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Table 2. Key trades in the construction process

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Table 3. Causes of task variation

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Table 4. Monthly work matrix of the Project 1

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Table 5. Project 1 adjacency matrix

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Table 6. Structural characteristic of networks

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