An Integrated Neutrosophic Group BWM-FMEA Approach for OHS Risk Assessment in Sustainable Construction Projects
DOI:
https://doi.org/10.11113/ijbes.v13.n3.1564Keywords:
Occupational health and safety risks, Sustainable construction projects, Neutrosophic Group BWM, Neutrosophic Group FMEA, Triangular single-valued Neutrosophic numbersAbstract
The expansion of the sustainable development concept in construction projects, coupled with the construction industry's high rates of safety accidents and job losses, underscores the critical need for effective Occupational Health and Safety (OHS) risk assessment in sustainable construction projects (SCPs). Poor safety performance, resulting from the lack of efficient and accurate risk assessment mechanisms, can reduce employee productivity and increase project cost and duration. Existing studies often overlook the integration of sustainability and health, safety, and environmental (HSE) dimensions with quantitative risk assessment under expert uncertainty. To address this gap, this research develops a hybrid Neutrosophic Group Best-Worst Method and Failure Modes and Effects Analysis (NG-BWM–NG-FMEA), incorporating expert weighting to quantify and prioritize OHS risks in Iran's SCPs. Thirteen experts participated via a focus group discussion. Key findings indicate that the top-ranked risks are: (1) insufficient employee safety skills due to inadequate training, (2) hazards from flawed design and site layout, and (3) occupational injuries and illnesses. The study proposes both reactive and preventive strategies to mitigate these and other prominent risks.
References
Alipour-Bashary, M., Ravanshadnia, M., Abbasianjahromi, H., & Asnaashari, E. (2021). A Hybrid Fuzzy Risk Assessment Framework for Determining Building Demolition Safety Index. KSCE Journal of Civil Engineering, 25(4): 1144-1162. DOI: http://dx.doi.org/10.1007/s12205-021-0812-4
Ardeshir, A., Ahmadi, P. F., & Bayat, H. (2018). A prioritization model for HSE risk assessment using combined failure mode, effect analysis, and fuzzy inference system: A case study in Iranian construction industry. International Journal of Engineering, 31(9): 1487-1497. DOI: http://dx.doi.org/10.5829/ije.2018.31.09c.03
Aven, T. (2016). Risk assessment and risk management: Review of recent advances on their foundation. European journal of operational research, 253(1): 1-13. DOI: https://doi.org/10.1016/j.ejor.2015.12.023
Ayber, S., & Erginel, N. (2019). Developing the neutrosophic fuzzy FMEA method as evaluating risk assessment tool. In International Conference on Intelligent and Fuzzy Systems 1130-1137. Springer, Cham. DOI: https://doi.org/10.1007/978-3-030-23756-1_133
Bai, X. P., & Zhao, Y. H. (2021). A novel method for occupational safety risk analysis of high-altitude fall accident in architecture construction engineering. Journal of Asian Architecture and Building Engineering, 20(3): 314-325. DOI: http://dx.doi.org/10.1080/13467581.2020.1796675
Belayutham, S., Gonzalez, V. A., & Yiu, T. W. (2016). A cleaner production-pollution prevention based framework for construction site induced water pollution. Journal of Cleaner Production, 135: 1363-1378. DOI: https://doi.org/10.1016/j.jclepro.2016.07.003
Chen, C., & Reniers, G. (2020). Chemical industry in China: The current status, safety problems, and pathways for future sustainable development. Safety science, 128: 104741. DOI: https://doi.org/10.1016/j.ssci.2020.104741
Dabbagh, R., & Yousefi, S. (2019). A hybrid decision-making approach based on FCM and MOORA for occupational health and safety risk analysis. Journal of safety research, 71: 111-123. DOI: https://doi.org/10.1016/j.jsr.2019.09.021
Elkington, J. (1997). The triple bottom line. Environmental management: Readings and cases, 2(1997): 49-66.
El-Sayegh, S. M., Manjikian, S., Ibrahim, A., Abouelyousr, A., & Jabbour, R. (2021). Risk identification and assessment in sustainable construction projects in the UAE. International Journal of Construction Management, 21(4): 327-336. DOI: http://dx.doi.org/10.1080/15623599.2018.1536963
Fang, H., Li, J., & Song, W. (2020). Failure mode and effects analysis: an integrated approach based on rough set theory and prospect theory. Soft Computing, 24(9): 6673-6685. https://link.springer.com/article/10.1007/s00500-019-04305-8
Fung, I. W., Tam, V. W., Lo, T. Y., & Lu, L. L. (2010). Developing a risk assessment model for construction safety. International Journal of Project Management, 28(6): 593-600. https://doi.org/10.1016/j.ijproman.2009.09.006
Gunduz, M., & Laitinen, H. (2018). Construction safety risk assessment with introduced control levels. Journal of Civil Engineering and Management, 24(1): 11-18. DOI: https://doi.org/10.3846/jcem.2018.284
Guo, X., Ji, J., Khan, F., Ding, L., & Yang, Y. (2021). Fuzzy Bayesian network based on an improved similarity aggregation method for risk assessment of storage tank accident. Process Safety and Environmental Protection, 149: 817-830. DOI: http://dx.doi.org/10.1016/j.psep.2020.07.030
Gürcanli, G. E., & Müngen, U. (2009). An occupational safety risk analysis method at construction sites using fuzzy sets. International Journal of Industrial Ergonomics, 39(2): 371-387. DOI: https://doi.org/10.1016/j.ergon.2008.10.006
Haktanir, E., & Kahraman, C. (2021). A Novel CRITIC Based Weighted FMEA Method: Application to COVID-19 Blood Testing Process. Journal of Multiple-Valued Logic & Soft Computing, 37. https://research.itu.edu.tr/en/publications/a-novel-critic-based-weighted-fmea-method-application-to-covid-19
Jeong, G., Kim, H., Lee, H. S., Park, M., & Hyun, H. (2022). Analysis of safety risk factors of modular construction to identify accident trends. Journal of Asian Architecture and Building Engineering, 21(3): 1040-1052. DOI: http://dx.doi.org/10.1080/13467581.2021.1877141
Karakhan, A. A., & Gambatese, J. A. (2017). Identification, quantification, and classification of potential safety risk for sustainable construction in the United States. Journal of Construction Engineering and Management, 143(7): 04017018. DOI: http://dx.doi.org/10.1061/(ASCE)CO.1943-7862.0001302
Kineber, A. F., Antwi‑Afari, M. F., Elghaish, F., Zamil, A. M. A., Alhusban, M., & Qaralleh, T. J. O. (2023). Benefits of implementing occupational health and safety management systems for the sustainable construction industry: A systematic literature review. Sustainability, 15(17): Article 12697. DOI: https://doi.org/10.3390/su151712697
Kim, S., Moore, A., Srinivasan, D., Akanmu, A., Barr, A., Harris-Adamson, C., ... & Nussbaum, M. A. (2019). Potential of exoskeleton technologies to enhance safety, health, and performance in construction: Industry perspectives and future research directions. IISE Transactions on Occupational Ergonomics and Human Factors, 7(3-4): 185-191. DOI: http://dx.doi.org/10.1080/24725838.2018.1561557
Kumru, M., & Kumru, P. Y. (2013). Fuzzy FMEA application to improve purchasing process in a public hospital. Applied Soft Computing, 13(1): 721-733. DOI: https://doi.org/10.1016/j.asoc.2012.08.007
Lavasani, S. M., Ramzali, N., Sabzalipour, F., & Akyuz, E. (2015). Utilisation of Fuzzy Fault Tree Analysis (FFTA) for quantified risk analysis of leakage in abandoned oil and natural-gas wells. Ocean Engineering, 108: 729-737. DOI: http://dx.doi.org/10.1016/j.oceaneng.2015.09.008
Liang, F., Brunelli, M., & Rezaei, J. (2020). Consistency issues in the best worst method: Measurements and thresholds. Omega, 96: 102175. DOI: https://doi.org/10.1016/j.omega.2019.102175
Lo, H. W., Shiue, W., Liou, J. J., & Tzeng, G. H. (2020). A hybrid MCDM-based FMEA model for identification of critical failure modes in manufacturing. Soft Computing, 24(20): 15733-15745. DOI: https://doi.org/10.1007/s00500-020-04903-x
Ma, M., Shen, L., Ren, H., Cai, W., & Ma, Z. (2017). How to Measure Carbon Emission Reduction in China’s Public Building Sector: Retrospective Decomposition Analysis Based on STIRPAT Model in 2000–2015. Sustainability, 9(10): 1744. DOI: https://doi.org/10.3390/su9101744
Malik, S., Fatima, F., Imran, A., Chuah, L. F., Klemeš, J. J., Khaliq, I. H., ... & Bokhari, A. (2019). Improved project control for sustainable development of construction sector to reduce environment risks. Journal of Cleaner Production, 240: 118214. DOI: http://dx.doi.org/10.1016/j.jclepro.2019.118214
Mohandes, S. R., & Zhang, X. (2021). Developing a Holistic Occupational Health and Safety risk assessment model: An application to a case of sustainable construction project. Journal of Cleaner Production, 291: 125934. DOI: https://doi.org/10.1016/j.jclepro.2021.125934
Murè, S., Comberti, L., & Demichela, M. (2017). How harsh work environments affect the occupational accident phenomenology? Risk assessment and decision making optimization. Safety science, 95: 159-170. DOI: https://doi.org/10.1016/j.ssci.2017.01.004
Pangemanan, D., Usman Latief, R., Hamzah, S., & Arifuddin, R. (2023). Study on the Application of Sustainable Construction in the Development of the Likupang Special Economic Zone. International Journal of Engineering Transactions C: Aspects, 36(1): 50-59. DOI: http://dx.doi.org/10.5829/IJE.2023.36.01A.07
Pinto, A. (2014). QRAM a qualitative occupational safety risk assessment model for the construction industry that incorporate uncertainties by the use of fuzzy sets. Safety Science, 63: 57-76. DOI: https://doi.org/10.1016/j.ssci.2013.10.019
Raviv, G., Shapira, A., & Fishbain, B. (2017). AHP-based analysis of the risk potential of safety incidents: Case study of cranes in the construction industry. Safety science, 91: 298-309. DOI: https://doi.org/10.1016/j.ssci.2016.08.027
Rezaei, J. (2016). Best-worst multi-criteria decision-making method: Some properties and a linear model. Omega, 64: 126-130. DOI: https://doi.org/10.1016/j.omega.2015.12.001
Rosenbaum, S., Toledo, M., & González, V. (2014). Improving environmental and production performance in construction projects using value-stream mapping: Case study. Journal of Construction Engineering and Management, 140(2): 04013045. DOI: http://dx.doi.org/10.1061/(ASCE)CO.1943-7862.0000793
Rowlinson, S., & Jia, Y. A. (2015). Construction accident causality: an institutional analysis of heat illness incidents on site. Safety science, 78: 179-189. DOI: http://dx.doi.org/10.1016/j.ssci.2015.04.021
Silvius, G., & Schipper, R. (2019). Planning project stakeholder engagement from a sustainable development perspective. Administrative sciences, 9(2): 46. DOI: https://doi.org/10.3390/admsci9020046
Smarandache, F. (1999). A unifying field in Logics: Neutrosophic Logic. In Philosophy. 1-141. American Research Press. https://philpapers.org/rec/SMAAUF
Soltanzadeh, A., Mahdinia, M., Omidi Oskouei, A., Jafarinia, E., Zarei, E., & Sadeghi‑Yarandi, M. (2022). Analyzing health, safety and environmental risks of construction projects using the fuzzy analytic hierarchy process: A field study based on a project management body of knowledge. Sustainability, 14(24): Article 16555. DOI: https://doi.org/10.3390/su142416555
Sui, Y., Ding, R., & Wang, H. (2020). A novel approach for occupational health and safety and environment risk assessment for nuclear power plant construction project. Journal of Cleaner Production, 258: 120945. DOI: https://doi.org/10.1016/j.jclepro.2020.120945
Tong, R., Cheng, M., Zhang, L., Liu, M., Yang, X., Li, X., & Yin, W. (2018). The construction dust-induced occupational health risk using Monte-Carlo simulation. Journal of cleaner production, 184: 598-608. DOI: http://dx.doi.org/10.1016/j.jclepro.2018.02.286
Xue, Y., & Deng, Y. (2020). Refined expected value decision rules under orthopair fuzzy environment. Mathematics, 8(3): 442. https://doi.org/10.3390/math8030442
Yan, H., Gao, C., Elzarka, H., Mostafa, K., & Tang, W. (2019). Risk assessment for construction of urban rail transit projects. Safety science, 118: 583-594. DOI: http://dx.doi.org/10.1016/j.ssci.2019.05.042
Yucesan, M., & Gul, M. (2021). Failure prioritization and control using the neutrosophic best and worst method. Granular Computing, 6(2): 435-449. https://link.springer.com/article/10.1007/s41066-019-00206-1
Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3): 338-353. DOI: https://doi.org/10.1016/S0019-9958(65)90241-X
Zhang, X., & Mohandes, S. R. (2020). Occupational Health and Safety in green building construction projects: A holistic Z-numbers-based risk management framework. Journal of cleaner production, 275: 122788. DOI: https://doi.org/10.1016/j.jclepro.2020.122788
Zhou, Z., Irizarry, J., & Lu, Y. (2018). A multidimensional framework for unmanned aerial system applications in construction project management. Journal of Management in Engineering, 34(3): 04018004. DOI: http://dx.doi.org/10.1061/(ASCE)ME.1943-5479.0000597
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