Application of Association Rule Mining and Social Network Analysis for Understanding Causality of Construction Defects

Sangdeok Lee,Yongwoon Cha,Sangwon Han,Changtaek Hyun

doi:10.3390/su11030618

Abstract

A construction defect can cause schedule delay, cost overrun and quality deterioration. In order to minimize these negative impacts of construction defects, this paper aims to analyze the causality of construction defects. Specifically, association rule mining (ARM) is used to quantify the interrelationships between defect causes, and social network analysis (SNA) is utilized to find out the most influential causes triggering generation of construction defects. The suggested approach was applied to 2949 defect instances in finishing work. Through this application, it was confirmed that the proposed approach can systematically identify and quantify causality among defect causes.

Highlights

A construction defect, which can have a negative impact on project performance such as schedule delay, cost overrun and quality deterioration, is a factor that should be prevented for successful accomplishment of a construction project [1,2]
Extending the theoretical foundation proposed by [20], this paper aims to systematically identify and quantify interrelated causality among construction defects through analysis of 2949 defect instances observed in finishing work which has a decisive impact on the overall quality of a building
Considering the practical and financial constraints imposed on construction firms, it is difficult for practitioners to identify and eliminate all possible causes of a potential defect

Summary

Introduction

A construction defect, which can have a negative impact on project performance such as schedule delay, cost overrun and quality deterioration, is a factor that should be prevented for successful accomplishment of a construction project [1,2]. Aljassmi et al [4], in addition, formulated a taxonomy of defect causes by using a fault-tree approach, which enables us to understand a mechanism of defect occurrence These studies contributed to better understand causality among defect causes and to provide a theoretical foundation for subsequent research. A remainder challenge to applying these models is that they require establishing rigid data collection protocols prior to their utilization to compile practitioner’s subjective judgments about defect causalities. Such extensive set-up efforts would not always be afforded by practitioners. These studies do not yet bear a link to the exploitation of currently available construction defects databases, but demonstrate ground-up approaches for defect data collection and formulation

Objectives

Methods

Conclusion