Safety Scheduling Through Integrated Accident Analysis Using Multiple Correspondence Analysis and Association Rule Mining: A Construction Engineering Perspective
Year: 2025
Type: article
Abstract: Construction accidents continue to threaten worker safety despite advances in management systems. Existing research catalogs accident attributes but rarely explains how triggers like human error, equipment failure, or procedural lapses interact with project types and tasks. This limits recognition of high-risk scenarios and hampers targeted prevention. To address this, a two-step framework combining Multiple Correspondence Analysis (MCA) and Association Rule Mining (ARM) is proposed. Using the Korean Construction Safety Management Integrated Information (CSI) database, MCA reduces dimensionality and clusters similar accident cases, while ARM extracts context-specific rules linking accident types, causes, and activities. The analysis reveals key patterns: (i) worker negligence during setup or formwork often leads to tool-related cuts; (ii) poor judgment or inadequate waste removal during excavation heightens hit or stuck incidents; and (iii) negligence frequently triggers hit and fall accidents during transportation, dismantling, and finishing. By mapping causes to operational risk factors, the framework supports actionable guidance for daily risk assessments. Safety professionals can align planned tasks with identified risks, enabling proactive interventions such as focused training, stricter supervision, and engineering controls. Thus, the MCA–ARM method establishes a data-driven foundation for improving safety decision-making and reducing construction accidents.
Source: Buildings
Institution: Dong-A University
Language: English
Subfield: Radiological and Ultrasound Technology
Field: Health Professions
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,137
Award: G7019246739
OpenAlex ID: W4415998341