Abstract
Risk assessment is one of the most effective actions in the safety management of demolition projects. This paper provides a framework to determine building demolition safety index (BDSI), which shows the safety level of a building being demolished. Two phases are involved in this study. In the first phase, 11 potential risks in building demolition and their influencing factors were identified, evaluated, and classified using a hybrid approach consisting of the Delphi method, Fine-Kinney method, fuzzy fault tree analysis (FTA), fuzzy technique for order preference by similarity to ideal solution (TOPSIS), and fuzzy inference system (FIS). In the second phase, a checklist of the most important safety factors and sub-factors in the demolition operation was provided, and the equations needed to calculate BDSI were presented. The first phase of the study was validated by comparing the study’s results with available demographic data from Tehran Construction Engineering Organization, Iran. The second phase was validated by calculating the BDSI for two buildings and evaluating the relationship between BDSI and safety level. BDSI is useful for building demolition projects because it allows project managers to have a more realistic view of the risk level of the project and accordingly take the necessary measures to prevent accidents.
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References
Abdelgawad M, Fayek AR (2010) Risk management in the construction industry using combined fuzzy FMEA and fuzzy AHP. Journal of Construction Engineering and Management 136(9):1028–1036, DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000210
Abdelgawad M, Fayek AR (2011) Fuzzy reliability analyzer: Quantitative assessment of risk events in the construction industry using fuzzy fault-tree analysis. Journal of Construction Engineering and Management 137(4):294–302, DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000285
Abdelgawad M, Fayek AR (2012) Comprehensive hybrid framework for risk analysis in the construction industry using combined failure mode and effect analysis, fault trees, event trees, and fuzzy logic. Journal of Construction Engineering and Management 138(5):642–651, DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000471
Abdollahzadeh G, Rastgoo S (2015) Risk assessment in bridge construction projects using fault tree and event tree analysis methods based on fuzzy logic. ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering 1(3), DOI: https://doi.org/10.1115/1.4030779
Ardeshir A, Amiri M, Ghasemi Y, Errington M (2014) Risk assessment of construction projects for water conveyance tunnels using fuzzy fault tree analysis. International Journal of Civil Engineering 12(4):396–412, http://ijce.iust.ac.ir/article-1-878-en.html
Atkinson AR, Westall R (2010) The relationship between integrated design and construction and safety on construction projects. Construction Management and Economics 28(9):1007–1017, DOI: https://doi.org/10.1080/01446193.2010.504214
Cao N (2006) Supply chain performance measurement in textile and apparel industries. PhD Thesis, Hong Kong Polytechnic University, Hong Kong
Chen C-T (2000) Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems 114(1):1–9, DOI: https://doi.org/10.1016/S0165-0114(97)00377-1
Ertaş H, Erdoğan AS (2017) An analysis of occupational accidents in demolition work. Civil Engineering and Architecture 5(2):37–51, DOI: https://doi.org/10.13189/cea.2017.050201
Gebrehiwet T, Luo H (2019) Risk level evaluation on construction project lifecycle using fuzzy comprehensive evaluation and TOPSIS. Symmetry 11(1):12, DOI: https://doi.org/10.3390/sym11010012
Gurcanli GE, Bilir S, Sevim M (2015) Activity based risk assessment and safety cost estimation for residential building construction projects. Safety Science 80:1–12, DOI: https://doi.org/10.1016/j.ssci.2015.07.002
Gürcanli GE, Müngen U (2013) Analysis of construction accidents in Turkey and responsible parties. Industrial Health 51(6):581–595, DOI: https://doi.org/10.2486/indhealth.2012-0139
Haghshenas SS, Neshaei MAL, Pourkazem P, Haghshenas SS (2016) The risk assessment of dam construction projects using fuzzy TOPSIS (case study: Alavian Earth Dam). Civil Engineering Journal 2(4):158–167, DOI: https://doi.org/10.28991/cej-2016-00000022
Hair JF, Anderson RE, Tatham RL, Black WC (1995) Multivariate data analysis with readings. Prentice Hall, Englewood Cliffs, NJ, USA
Hallowell MR, Gambatese JA (2009) Construction safety risk mitigation. Journal of Construction Engineering and Management 135(12):1316–1323, DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000107
Hallowell MR, Gambatese JA (2010) Qualitative research: Application of the Delphi method to CEM research. Journal of Construction Engineering and Management 136(1):99–107, DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000137
Hwang C-L, Yoon K (1981) Methods for multiple attribute decision making. In: Multiple attribute decision making. Springer, Berlin, Germany, 58–191, DOI: https://doi.org/10.1007/978-3-642-48318-9_3
Ilbahar E, Karaşan A, Cebi S, Kahraman C (2018) A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP & fuzzy inference system. Safety Science 103:124–136, DOI: https://doi.org/10.1016/j.ssci.2017.10.025
Jordan E, Javernick-Will A (2013) Indicators of community recovery: Content analysis and Delphi approach. Natural Hazards Review 14(1):21–28, DOI: https://doi.org/10.1061/(ASCE)NH.1527-6996.0000087
KarimiAzari A, Mousavi N, Mousavi SF, Hosseini S (2011) Risk assessment model selection in construction industry. Expert Systems with Applications 38(8):9105–9111, DOI: https://doi.org/10.1016/j.eswa.2010.12.110
Kaya T, Kahraman C (2011) An integrated fuzzy AHP-ELECTRE methodology for environmental impact assessment. Expert Systems with Applications 38(7):8553–8562, DOI: https://doi.org/10.1016/j.eswa.2011.01.057
Kinney GF, Wiruth A (1976) Practical risk analysis for safety management. Naval Weapons Center, China Lake, CA, USA
Lee P-C, Wei J, Ting H-I, Lo T-P, Long D, Chang L-M (2019) Dynamic analysis of construction safety risk and visual tracking of key factors based on behavior-based safety and building information modeling. KSCE Journal of Civil Engineering 23(10):4155–4167, DOI: https://doi.org/10.1007/s12205-019-0283-z
Maghsoodi AI, Khalilzadeh M (2018) Identification and evaluation of construction projects’ critical success factors employing fuzzy-topsis approach. KSCE Journal of Civil Engineering 22(5):1593–1605, DOI: https://doi.org/10.1007/s12205-017-1970-2
Mamdani EH, Assilian S (1975) An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies 7(1):1–13, DOI: https://doi.org/10.1016/S0020-7373(75)80002-2
MCLS (2011) Safety at construction sites. Ministry of Cooperatives Labour and Social Welfare. Retrieved September 5, 2019, https://www.mcls.gov.ir/en/news/23213
Mohammadi A, Tavakolan M (2013) Construction project risk assessment using combined fuzzy and FMEA. 2013 joint IFSA world congress and NAFIPS annual meeting (IFSA/NAFIPS), June 24–28, Edmonton, AB, Canada, 232–237, DOI: https://doi.org/10.1109/IFSA-NAFIPS.2013.6608405
Mohandes SR, Zhang X (2019) Towards the development of a comprehensive hybrid fuzzy-based occupational risk assessment model for construction workers. Safety Science 115:294–309, DOI: https://doi.org/10.1016/j.ssci.2019.02.018
Nieto-Morote A, Ruz-Vila F (2011) A fuzzy approach to construction project risk assessment. International Journal of Project Management 29(2):220–231, DOI: https://doi.org/10.1016/j.ijproman.2010.02.002
Norouzi A, Namin HG (2019) A hybrid fuzzy TOPSIS — Best worst method for risk prioritization in megaprojects. Civil Engineering Journal 5(6):1257–1272, DOI: https://doi.org/10.28991/cej-2019-03091330
Patel D, Jha K (2017) Developing a process to evaluate construction project safety hazard index using the possibility approach in India. Journal of Construction Engineering and Management 143(1): 04016081, DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001205
Ravanshadnia M, Rajaie H, Abbasian HR (2010) Hybrid fuzzy MADM project-selection model for diversified construction companies. Canadian Journal of Civil Engineering 37(8):1082–1093, DOI: https://doi.org/10.1139/L10-048
Rozenfeld O, Sacks R, Rosenfeld Y, Baum H (2010) Construction job safety analysis. Safety Science 48(4):491–498, DOI: https://doi.org/10.1016/j.ssci.2009.12.017
Shanmugapriya S, Subramanian K (2016) Developing a PLS path model to investigate the factors influencing safety performance improvement in construction organizations. KSCE Journal of Civil Engineering 20(5):1138–1150, DOI: https://doi.org/10.1007/s12205-015-0442-9
Sousa V, Almeida NM, Dias LA (2015) Risk-based management of occupational safety and health in the construction industry — Part 2: Quantitative model. Safety Science 74:184–194, DOI: https://doi.org/10.1016/j.ssci.2015.01.003
Stankovic M, Stankovic V (2013) Comparative analysis of methods for risk assessment-Kinney and Auva. Safety Engineering 3(3):129–136, DOI: https://doi.org/10.7562/SE2013.3.03.04
Tam C, Zeng S, Deng Z (2004) Identifying elements of poor construction safety management in China. Safety Science 42(7):569–586, DOI: https://doi.org/10.1016/j.ssci.2003.09.001
Tang J, Liu X, Wang W (2020) A hybrid risk prioritization method based on generalized TODIM and BWM for Fine-Kinney under interval type-2 fuzzy environment. Human and Ecological Risk Assessment: An International Journal 1–26, DOI: https://doi.org/10.1080/10807039.2020.1789840
Verma AK, Srividya A, Gaonkar RP (2006) Fuzzy-reliability engineering: Concepts and applications. Narosa Publishing, New Delhi, India, 88–127
Wang W, Liu X, Qin Y (2018) A fuzzy Fine-Kinney-based risk evaluation approach with extended MULTIMOORA method based on Choquet integral. Computers & Industrial Engineering 125:111–123, DOI: https://doi.org/10.1016/j.cie.2018.08.019
Zaharuddin W, Paraskevas I, Liu C (2009) Accident avoidance importance for building demolition. In: CIB W099 2009: Working together: Planning, designing and building a healthy and safe construction industry. RMIT University, Melbourne, Australia, 9–14
Zeng J, An M, Smith NJ (2007) Application of a fuzzy based decision making methodology to construction project risk assessment. International Journal of Project Management 25(6):589–600, DOI: https://doi.org/10.1016/j.ijproman.2007.02.006
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Alipour-Bashary, M., Ravanshadnia, M., Abbasianjahromi, H. et al. A Hybrid Fuzzy Risk Assessment Framework for Determining Building Demolition Safety Index. KSCE J Civ Eng 25, 1144–1162 (2021). https://doi.org/10.1007/s12205-021-0812-4
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DOI: https://doi.org/10.1007/s12205-021-0812-4