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Classification of construction hazards for a universal hazard identification methodology

    Matej Mihić   Affiliation

Abstract

Hazard identification in the construction industry is subject to a larger number of variables and unknowns than in other manufacturing industries making the hazard identification process more difficult and resulting in many injuries and fatalities. Moreover, previous research identified a research gap with regards to a universal hazard identification method. The results presented in this paper are a prerequisite for the development of such a method. Specifically, this paper proposes a novel classification of hazards in order to enable a more accurate hazard identification process which can take all possible hazards into consideration. Based on the theoretical framework, three hazard types are proposed in the research: self-induced hazards, peer-induced hazards, and global hazards. This classification is based on who is the source (who causes) the hazards in relation to who is affected by the hazards. Such classification was not identified in previous literature. This research also has practical implications. Such classification of hazards may influence safety experts to more actively focus on peer-induced hazards which are the hardest to identify. Finally, the outputs of the entire research should enable a more accurate and comprehensive hazard identification resulting in reduced injury and fatality rates in the construction industry.

Keyword : health and safety, construction hazards, hazard identification, hazard classification, self-induced hazards, peer-induced hazards, global hazards

How to Cite
Mihić, M. (2020). Classification of construction hazards for a universal hazard identification methodology. Journal of Civil Engineering and Management, 26(2), 147-159. https://doi.org/10.3846/jcem.2020.11932
Published in Issue
Feb 7, 2020
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This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Abdelhamid, T. S., & Everett, J. G. (2000). Identifying root causes of construction accidents. Journal of Construction Engineering and Management, 126(1), 52–60. https://doi.org/10.1061/(ASCE)0733-9364(2000)126:1(52)

Al-Aubaidy, N. A., Caldas, C. H., & Mulva, S. P. (2019). Assessment of underreporting factors on construction safety incidents in US construction projects. International Journal of Construction Management. https://doi.org/10.1080/15623599.2019.1613211

Alizadehsalehi, S., Yitmen, I., Celik, T., & Arditi, D. (2018). The effectiveness of an integrated BIM/UAV model in managing safety on construction sites. International Journal of Occupational Safety and Ergonomics, 1–16. https://doi.org/10.1080/10803548.2018.1504487

Bansal, V. K. (2011). Application of geographic information systems in construction safety planning. International Journal of Project Management, 29(1), 66–77. https://doi.org/10.1016/j.ijproman.2010.01.007

Baradan, S., & Usmen, M. A. (2006). Comparative injury and fatality risk analysis of building trades. Journal of Construction Engineering and Management, 132(5), 533–539. https://doi.org/10.1061/(ASCE)0733-9364(2006)132:5(533)

Carter, G., & Smith, S. D. (2006). Safety hazard identification on construction projects. Journal of Construction Engineering and Management, 132(2), 197–205. https://doi.org/10.1061/(ASCE)0733-9364(2006)132:2(197)

Cerić, A. (2014). Upravljanje rizicima. In Hrvatski Graditeljski Forum, Zagreb, Croatia.

Chen, A., Golparvar-Fard, M., & Kleiner, B. (2013). Design and development of SAVES: A construction safety training augmented virtuality environment for hazard recognition and severity identification. In ASCE International Workshop on Computing in Civil Engineering (pp. 841–848). American Society of Civil Engineers. https://doi.org/10.1061/9780784413029.105

Collins, R., Zhang, S., Kim, K., & Teizer, J. (2014). Integration of safety risk factors in BIM for scaffolding construction. In 2014 International Conference on Computing in Civil and Building Engineering (pp. 307–314). American Society of Civil Engineers. https://doi.org/10.1061/9780784413616.039

Cox, L. A. (2008). What’s wrong with risk matrices? Risk Analysis, 28(2), 497–512. https://doi.org/10.1111/j.1539-6924.2008.01030.x

Dharmapalan, V., Gambatese, J., Fradella, J., & Moghaddam Vahed, A. (2014). Quantification and assessment of safety risk in the design of multistory buildings. Journal of Construction Engineering and Management, 141(4), 04014090. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000952

Eurostat. (2015). Accidents at work statistics. http://ec.europa.eu/eurostat/statistics-explained/index.php/Accidents_at_work_statistics

Godfaurd, J., & Abdulkadir, G. (2011). Integrating BIM and planning software for health and safety site induction. In COBRA 2011, The Royal Institution of Chartered Surveyors International Research Conference (pp. 1043–1053), Manchester, UK.

Gunduz, M., & Laitinen, H. (2018). Construction safety risk assessment with introduced control levels. Journal of Civil Engineering and Management, 24(1), 11–18. https://doi.org/10.3846/jcem.2018.284

Hallowell, M., & Gambatese, J. (2009). Activity-based safety risk quantification for concrete formwork construction. Journal of Construction Engineering and Management, 135(10), 990–998. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000071

Hatefi, S. M., & Tamošaitienė, J. (2019). An integrated fuzzy DEMATEL-fuzzy ANP model for evaluating construction projects by considering interrelationships among risk factors. Journal of Civil Engineering and Management, 25(2), 114–131. https://doi.org/10.3846/jcem.2019.8280

Health and Safety Executive. (2016). Health and safety statistics for the construction sector in Great Britain. http://www.hse.gov.uk/statistics/industry/construction/index.htm

International Labor Organization. (2005). World day for safety and health at work 2005: a background paper. http://www.ilo.org/public/english/bureau/inf/dowload/sh_background.pdf

Jannadi, O., & Almishari, S. (2003). Risk assessment in construction. Journal of Construction Engineering and Management, 129(5), 492–500. https://doi.org/10.1061/(ASCE)0733-9364(2003)129:5(492)

Kim, K., & Cho, Y. (2015). BIM-based planning of temporary structures for construction safety. In 2015 International Workshop on Computing in Civil Engineering 2015 (pp. 436–444). American Society of Civil Engineers. https://doi.org/10.1061/9780784479247.054

Kim, S. D. (2017). Characterization of unknown unknowns using separation principles in case study on Deepwater Horizon oil spill. Journal of Risk Research, 20(1), 151–168. https://doi.org/10.1080/13669877.2014.983949

Korea Occupational Safety and Health Agency. (2003). Annual report: Fatal accident cases, 2001–2003.

Martínez-Aires, M. D., López-Alonso, M., & Martínez-Rojas, M. (2018). Building information modeling and safety management: A systematic review. Safety Science, 101, 11–18. https://doi.org/10.1016/j.ssci.2017.08.015

Mihić, M., Cerić, A., & Završki, I. (2018). Developing construction hazard database for automated hazard identification process. Technical Gazette, 25(6), 1761–1769. https://doi.org/10.17559/TV-20180417105624

Mihić, M., Vukomanović, M., & Završki, I. (2019). Review of previous applications of innovative information technologies in construction health and safety. Organization, Technology and Management in Construction, 11(1), 16. https://doi.org/10.2478/otmcj-2019-0004

National Safety Council. (1997). Sample JHA.

Niu, Y., Lu, W., Xue, F., Liu, D., Chen, K., Fang, D., & Anumba, C. (2019). Towards the “third wave”: An SCO-enabled occupational health and safety management system for construction. Safety Science, 111, 213–223. https://doi.org/10.1016/j.ssci.2018.07.013

NNC Limited. (2003). The development of a knowledge based system to deliver health and safety information to designers in the construction industry. In Research report 173 (pp. 89). Norwich, UK: Health & Safety Executive.

Pinto, A., Nunes, I. L., & Ribeiro, R. A. (2011). Occupational risk assessment in construction industry – overview and reflection. Safety Science, 49(5), 616–624. https://doi.org/10.1016/j.ssci.2011.01.003

Raheem, A. A., & Hinze, J. W. (2014). Disparity between construction safety standards: A global analysis. Safety Science, 70, 276–287. https://doi.org/10.1016/j.ssci.2014.06.012

Roberts, J. (2013). Organizational ignorance: Towards a managerial perspective on the unknown. Management Learning, 44(3), 215–236. https://doi.org/10.1177/1350507612443208

Rozenfeld, O., Sacks, R., & Rosenfeld, Y. (2009). ‘CHASTE’: construction hazard assessment with spatial and temporal exposure. Construction Management and Economics, 27(7), 625–638. https://doi.org/10.1080/01446190903002771

Rozenfeld, O., Sacks, R., Rosenfeld, Y., & Baum, H. (2010). Construction job safety analysis. Safety Science, 48(4), 491–498. https://doi.org/10.1016/j.ssci.2009.12.017

Sacks, R., Rozenfeld, O., & Rosenfeld, Y. (2009). Spatial and temporal exposure to safety hazards in construction. Journal of Construction Engineering and Management, 135(8), 726–736. https://doi.org/10.1061/(ASCE)0733-9364(2009)135:8(726)

Teizer, J., Allread, B. S., Fullerton, C. E., & Hinze, J. (2010). Autonomous pro-active real-time construction worker and equipment operator proximity safety alert system. Automation in Construction, 19(5), 630–640. https://doi.org/10.1016/j.autcon.2010.02.009

Teizer, J., Venugopal, M., & Walia, A. (2008). Ultrawideband for automated real-time three-dimensional location sensing for workforce, equipment, and material positioning and tracking. Transportation Research Record: Journal of the Transportation Research Board, 2081, 56–64. https://doi.org/10.3141/2081-06

U.S. Bureau of Labor Statistics. (2018). National census of fatal occupational injuries in 2017.

U.S. Department of Labor. (2002). Job hazard analysis. Washington, DC.

Wang, H.-H., & Boukamp, F. (2011). Ontology-based representation and reasoning framework for supporting job hazard analysis. Journal of Computing in Civil Engineering, 25(6), 442–456. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000125

Zhang, S. (2014). Integrating safety and BIM: automated construction hazard identification and prevention (PhD thesis). Georgia Institute of Technology.

Zhang, S., Teizer, J., Lee, J.-K., Eastman, C. M., & Venugopal, M. (2013). Building information modeling (BIM) and safety: Automatic safety checking of construction models and schedules. Automation in Construction, 29, 183–195. https://doi.org/10.1016/j.autcon.2012.05.006

Zhang, S., Boukamp, F., & Teizer, J. (2015a). Ontology-based semantic modeling of construction safety knowledge: Towards automated safety planning for job hazard analysis (JHA). Automation in Construction, 52, 29–41. https://doi.org/10.1016/j.autcon.2015.02.005

Zhang, S., Sulankivi, K., Kiviniemi, M., Romo, I., Eastman, C. M., & Teizer, J. (2015b). BIM-based fall hazard identification and prevention in construction safety planning. Safety Science, 72, 31–45. https://doi.org/10.1016/j.ssci.2014.08.001

Zhou, Z., Goh, Y. M., & Li, Q. (2015). Overview and analysis of safety management studies in the construction industry. Safety Science, 72, 337–350. https://doi.org/10.1016/j.ssci.2014.10.006

Zhou, Z., Li, C., Mi, C., & Qian, L. (2019). Exploring the potential use of near-miss information to improve construction safety performance. Sustainability, 11(5), 1264. https://doi.org/10.3390/su11051264

Zolfagharian, S., Irizarry, J., Ressang, A., Nourbakhsh, M., & Gheisari, M. (2014). Automated safety planning approach for residential construction sites in Malaysia. International Journal of Construction Management, 14(3), 134–147. https://doi.org/10.1080/15623599.2014.926190