التفاصيل البيبلوغرافية
| العنوان: |
Construction of a Bayesian network model for improving the safety performance of electrical and mechanical (EandM) works in repair, maintenance, alteration and addition (RMAA) projects |
| المؤلفون: |
Chan, Albert P C, Wong, Francis K.W., Hon, Carol, Choi, Tracy N.Y. |
| المصدر: |
Safety Science |
| بيانات النشر: |
Elsevier |
| سنة النشر: |
2020 |
| المجموعة: |
Queensland University of Technology: QUT ePrints |
| الوصف: |
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. |
| نوع الوثيقة: |
article in journal/newspaper |
| وصف الملف: |
application/pdf |
| اللغة: |
unknown |
| Relation: |
https://eprints.qut.edu.au/202788/1/64832101.pdf; Chan, Albert P C, Wong, Francis K.W., Hon, Carol, & Choi, Tracy N.Y. (2020) Construction of a Bayesian network model for improving the safety performance of electrical and mechanical (EandM) works in repair, maintenance, alteration and addition (RMAA) projects. Safety Science, 131, Article number: 104893.; https://eprints.qut.edu.au/202788/; Institute for Future Environments; Science & Engineering Faculty; School of Built Environment; Faculty of Business & Law; Centre for Tropical Crops and Biocommodities |
| الاتاحة: |
https://eprints.qut.edu.au/202788/ |
| Rights: |
free_to_read ; http://creativecommons.org/licenses/by-nc-nd/2.5/ ; 2020 Elsevier Ltd ; This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au |
| رقم الانضمام: |
edsbas.311EBFFE |
| قاعدة البيانات: |
BASE |