Construction of a Bayesian network model for improving the safety performance of electrical and mechanical (E&M) works in repair, maintenance, alteration and addition (RMAA) projects

Albert P.C. Chan, Francis K.W. Wong, Carol K.H. Hon, Tracy N.Y. Choi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)

Abstract

The safety concern and volume of repair, maintenance, alteration and addition (RMAA) works have significantly increased in recent years. RMAA works include a variety of work trades. Electrical and mechanical (E&M) works are regarded as one of the most hazardous trades with numerous complex activities. However, the research on the safety of E&M works in RMAA projects is limited. This study aims to develop a Bayesian network (BN) model that encapsulates the interrelationships between safety factors and safety performance. Survey data are analysed with factor and BN analyses to construct a BN model. Findings show that alcohol consumption and smoking habits of workers exert a considerable influence on the safety performance of workers. A strategy via controlling multiple factors (joint strategies) may even improve safety performance. Analytical results indicate the effectiveness of a joint control of alcohol and smoking habit, safety inspection and procedures factors would be the most effective strategy to improve safety performance. The significance of this study lies in the proffering of a BN model that reveals the interrelationships of the safety factors and safety performance of E&M works in RMAA projects. The findings will help in formulating effective safety management strategies to improve the safety of RMAA works. The BN model can be a practical technique to diagnose effective safety measures for improving safety performance. The research outcomes would be valuable to key project stakeholders of E&M works to achieve better safety performance and bring tremendous value in better safeguarding E&M workers’ health and safety.

Original languageEnglish
Article number104893
JournalSafety Science
Volume131
DOIs
Publication statusPublished - Nov 2020

Keywords

  • Accident analysis
  • Bayesian networks approach
  • Construction
  • Electrical and mechanical (E&M) Works
  • Safety management

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Safety Research
  • Public Health, Environmental and Occupational Health

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