Application of fuzzy fault tree analysis to identify factors influencing construction labor productivity: a high-rise building case study
Abstract
The aim of this research is to develop a systematic approach to identify and prioritize the most influencing factors on labor productivity in a construction project, with respect to their interrelations, and also investigate different scenarios which can affect it. In the first step, factors influencing construction labor productivity were identified through reviewing previous researches. Applying a group of experts, the most important factors were then determined using their relative importance index in the second step. In the third step, the interrelations among factors were determined through several sessions and interviewing those experts. Finally, the efficiency of the proposed methodology is proved by implementing in a real high rise building construction project. In this step, the selected factors from previous steps were used subsequently for analyzing their impact on labor productivity through fuzzy fault tree analysis. The probability of occurrence of events was determined according to the opinions of four members of the project management team who involved in that project. The most critical causes were also identified using importance analysis. It is believed that using the proposed methodology, appropriate response strategies could be adopted against the identified critical events to enhance the overall productivity of a construction project.
Keyword : construction management, quantitative risk analysis, labor productivity, influential factors, fault tree analysis, fuzzy set theory
How to Cite
Shoar, S., & Banaitis, A. (2019). Application of fuzzy fault tree analysis to identify factors influencing construction labor productivity: a high-rise building case study. Journal of Civil Engineering and Management, 25(1), 41-52. https://doi.org/10.3846/jcem.2019.7785
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Durdyev, S., & Ismail, S. (2017). The build-operate-transfer model as an infrastructure privatisation strategy for Turkmenistan. Utilities Policy, 48, 195-200. https://doi.org/10.1016/j.jup.2016.12.002
Durdyev, S., & Mbachu, J. (2018). Key constraints to labour productivity in residential building projects: Evidence from Cambodia. International Journal of Construction Management, 18(5), 385-393. https://doi.org/10.1080/15623599.2017.1326301
Durdyev, S., Ismail, S., & Kandymov, N. (2018). Structural equation model of the factors affecting construction labor productivity. Journal of Construction Engineering and Management, 144(4), 1-11. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001452
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El-Gohary, K., & Aziz, R. (2014). Factors influencing construction labor productivity in Egypt. Journal of Management in Engineering, 30(1), 1-9. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000168
Enshassi, A., Mohamed, S., Abu Mustafa, Z., & Mayer, P. E. (2007). Factors affecting labour productivity in building projects in the Gaza Strip. Journal of Civil Engineering and Management, 13(4), 245-254.
Enshassi, A., Mohamed, S., Mayer, P., & Abed, K. (2007). Benchmarking masonry labor productivity. International Journal of Productivity and Performance Management, 56(4), 358-368. https://doi.org/10.1108/17410400710745342
Fagbenle, O. I., Ogunde, A. O., & Owolabi, J. D. (2011). Factors affecting the performance of labour in Nigerian construction sites. Mediterranean Journal of Social Sciences, 2(2), 251-257.
Fayek, A. R. (2011). Fuzzy hybrid modeling for strategic construction analysis and delivery. Natural Sciences and Engineering Research Council of Canada Industrial Research Chair proposal, Department of Civil and Environmental. University of Alberta, Edmonton, Alta.
Field, A. (2009). Discovering statistics using SPSS. Thousand Oaks, California, CA.: Sage publications.
Franke, U., Flores, W. R., & Johnson, P. (2009). Enterprise architecture dependency analysis using fault trees and Bayesian networks. In Proceedings of the 42nd Annual Simulation Symposium (ANSS 2009), (pp. 209-216). San Diego, CA: Society for Computer Simulation International
Fulford, R., & Standing, C. (2014). Construction industry productivity and the potential for collaborative practice. International Journal of Project Management, 32(2), 315-326. https://doi.org/10.1016/j.ijproman.2013.05.007
Ghoddousi, P., & Hosseini, M. R. (2012). A survey of the factors affecting the productivity of construction projects in Iran. Technological and Economic Development of Economy, 18(1), 99-116. https://doi.org/10.3846/20294913.2012.661203
Gündüz, U., & Kaya, T. (2017). Regional employment generation potential of the Turkish labor market: An inter-sectoral perspective. Technological and Economic Development of Economy, 23(5), 726-741. https://doi.org/10.3846/20294913.2015.1015110
Hafez, S. M., Aziz, R. F., Morgan, E. S., Abdullah, M. M., & Ahmed, E. K. (2014). Critical factors affecting construction labor productivity in Egypt. American Journal of Civil Engineering, 2(2), 35-40. https://doi.org/10.11648/j.ajce.20140202.14
Hanna, A. S., Taylor, C. S., & Sullivan, K. T. (2005). Impact of extended overtime on construction labor. Journal of Construction Engineering and Management, 131(6), 734-739. https://doi.org/10.1061/(ASCE)0733-9364(2005)131:6(734)
Heravi, G., & Eslamdoost, E. (2015). Applying artificial neural networks for measuring and predicting construction-labor productivity. Journal of Construction Engineering and Management, 141(10), 1-11. https://doi.org/10.1061/(ASCE)0733-9364(2005)131:6(734)
Hickson, B. G., & Ellis, L. A. (2014). Factors affecting construction labour productivity in Trinidad and Tobago. The Journal of the Association of Professional Engineers of Trinidad and Tobago, 42(1), 4-11.
Hiyassat, M. A., Hiyari, M. A., & Sweis, G. J. (2016). Factors affecting construction labour productivity: A case study of Jordan. International Journal of Construction Management, 16(2), 138-149. https://doi.org/10.1080/15623599.2016.1142266
Hoyland, A., & Rausand, M. (2004). System reliability theory models and statistical methods (2nd ed.). Hoboken, New Jersey: John Wiley and Sons.
Hwang, B. G., Zhao, X., & Do, T. H. V. (2014). Influence of trade‐level coordination problems on project productivity. Project Management Journal, 45(5), 5-14. https://doi.org/10.1002/pmj.21445
Iverson, S., Kerkering, J., Coleman, P., & Spokane, W. (2001). Using fault tree analysis to focus mine safety research. In Proceedings of the 108th Annual meeting of the Society for Mining, Metallurgy, and Exploration (pp. 1-10).
Jarkas, A. (2012). Buildability factors influencing concreting labour productivity. Journal of Construction Engineering and Management, 138(1), 89-97. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000404
Jarkas, A. M. (2015). Factors influencing labour productivity in Bahrain’s construction industry. International Journal of Construction Management, 15(1), 94-108. https://doi.org/10.1080/15623599.2015.1012143
Jarkas, A. M., & Bitar, C. G. (2012). Factors affecting construction labour productivity in Kuwait. Journal of Construction Engineering and Management, 138(7), 811-820. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000501
Jarkas, A. M., Al Balushi, R. A., & Raveendranath, P. K. (2015). Determinants of construction labour productivity in Oman. International Journal of Construction Management, 15(4), 332-344. https://doi.org/10.1080/15623599.2015.1094849
Kales, P. (2006). Reliability for technology, engineering and management. Taipei: Pearson Education Taiwan Ltd.
Kaming, P. F., Holt, G. D., Kometa, S. T., & Olomolaiye, P. O. (1998). Severity diagnosis of productivity problems – A reliability analysis. International Journal of Project Management, 16(2), 107-113. https://doi.org/10.1016/S0263-7863(97)00036-7
Karimi, H., Taylor, T. R. B., & Goodrum, P. M. (2017). Analysis of the impact of craft labour availability on North American construction project productivity and schedule performance. Construction Management and Economics, 35(6), 368-380. https://doi.org/10.1080/01446193.2017.1294257
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. https://doi.org/10.1016/j.oceaneng.2015.09.008
Lindhe, A., Rosen, L., Norberg, T., & Bergstedt, O. (2009). Fault tree analysis for integrated and probabilistic risk analysis of drinking water systems. Water Research, 43(6), 1641-1653. https://doi.org/10.1016/j.watres.2008.12.034
Ma, L., Liu, C., & Reed, R. (2017). The impacts of residential construction and property prices on residential construction outputs: An inter-market equilibrium approach. International Journal of Strategic Property Management, 21(3), 296-306. https://doi.org/10.3846/1648715X.2016.1255675
Nasirzadeh, F., & Nojedehi, P. (2013). Dynamic modeling of labor productivity in construction projects. International Journal of Project Management, 31(6), 903-911. https://doi.org/10.1016/j.ijproman.2012.11.003
O’Connor, P. D. T. (2002). Practical reliability engineering. New York: John Wiley & Sons Inc.
Oglesby, C., Parker, H., & Howell, G. (1989). Productivity improvement in construction. New York: McGraw-Hill.
Parchami Jalal, M., & Shoar, S. (2017). A hybrid SD-DEMATEL approach to develop a delay model for construction projects. Engineering, Construction and Architectural Management, 24(4), 629-651. https://doi.org/10.1108/ECAM-02-2016-0056
Robles, G., Stifi, A., Ponz-Tienda, J. L., & Gentes, S. (2014). Labor productivity in the construction industry – Factors influencing the Spanish construction labor productivity. International Journal of Civil and Environmental Engineering, 8(10), 1061-1070.
Shoar, S., & Nazari, A. (2018). An optimization framework for risk response actions selection using hybrid ACO and FTOPSIS. Scientia Iranica (in Press). https://doi.org/10.24200/sci.2018.20225
Shoar, S., Zarandi, H. R., Nasirzadeh, F., & Cheshmikhani, E. (2017). Fast fault tree analysis for hybrid uncertainties using stochastic logic implemented on field‐programmable gate arrays: An application in quantitative assessment and mitigation of welding defects risk. Quality and Reliability Engineering International, 33, 1367-1385. https://doi.org/10.1002/qre.2110
Tanaka, H., Fan, T. L., Lai, F. S., & Toguchi, K. (1983). Fault-tree analysis by fuzzy probability. IEEE Transactions on Reliability, 32(5), 453-457. https://doi.org/10.1109/TR.1983.5221727
Yi, W., & Chan, A. P. C. (2014). Critical review of labor productivity research in construction journals. Journal of Management in Engineering, 30(2), 214-225. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000194
Zadeh, L. (1965). Fuzzy sets. Information and Control, 8(3), 338-353. https://doi.org/10.1016/S0019-9958(65)90241-X
Zhang, L., Skibniewski, M. J., Wu, X., Chen, Y., & Deng, Q. (2014). A probabilistic approach for safety risk analysis in metro construction. Safety Science, 63, 8-17. https://doi.org/10.1016/j.ssci.2013.10.016
Abdelgawad, M., & Fayek, A. R. (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. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000285
Alaghbari, W., Al-Sakkaf, A. A., & Sultan, B. (2019). Factors affecting construction labour productivity in Yemen. International Journal of Construction Management, 19(1), 79-91. https://doi.org/10.1080/15623599.2017.1382091
Alinaitwe, H. M., Mwakali, J. A., & Hansson, B. (2007). Factors affecting the productivity of building craftsmen – Studies of Uganda. Journal of Civil Engineering and Management, 13(3), 169-176. https://doi.org/10.3846/13923730.2007.9636434
Alkay, E., Watkins, C., & Keskin, B. (2018). Explaining spatial variation in housing construction activity in Turkey. International Journal of Strategic Property Management, 22(2), 119-130. https://doi.org/10.3846/ijspm.2018.443
Borcherding, J. D., & Liou, F. S. (1986). Work sampling can predict unit rate productivity. Journal of Construction Engineering and Management, 112(1), 90-103. https://doi.org/10.1061/(ASCE)0733-9364(1986)112:1(90)
Chigara, B., & Moyo, T. (2014). Factors affecting labor productivity on building projects in Zimbabwe. International Journal of Architecture, Engineering and Construction, 3(1), 57-65. https://doi.org/10.7492/IJAEC.2014.005
Chin, K. S., Wang, Y. M., Poon, G. K. K., & Yang, J. B. (2009). Failure mode and effects analysis using a group-based evidential reasoning approach. Computers & Operations Research, 36(6), 1768-1779. https://doi.org/10.1016/j.cor.2008.05.002
Dai, J., Goodrum, P. M., & Maloney, W. F. (2009). Construction craft workers’ perceptions of the factors affecting their productivity. Journal of Construction Engineering and Management, 135(3), 217-226. https://doi.org/10.1061/(ASCE)0733-9364(2009)135:3(217)
Dai, J., Goodrum, P. M., Maloney, W. F., & Srinivasan, C. (2009). Latent structures of the factors affecting construction labor productivity. Journal of Construction Engineering and Management, 135(5), 397-406. https://doi.org/10.1061/(ASCE)0733-9364(2009)135:5(397)
Durdyev, S., & Ismail, S. (2017). The build-operate-transfer model as an infrastructure privatisation strategy for Turkmenistan. Utilities Policy, 48, 195-200. https://doi.org/10.1016/j.jup.2016.12.002
Durdyev, S., & Mbachu, J. (2018). Key constraints to labour productivity in residential building projects: Evidence from Cambodia. International Journal of Construction Management, 18(5), 385-393. https://doi.org/10.1080/15623599.2017.1326301
Durdyev, S., Ismail, S., & Kandymov, N. (2018). Structural equation model of the factors affecting construction labor productivity. Journal of Construction Engineering and Management, 144(4), 1-11. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001452
Durdyev, S., Zavadskas, K. E., Thurnell, D., Banaitis, A., & Ihtiyar, A. (2018). Sustainable construction industry in Cambodia: Awareness, drivers and barriers. Sustainability, 10(2), 392. https://doi.org/10.3390/su10020392
El-Gohary, K., & Aziz, R. (2014). Factors influencing construction labor productivity in Egypt. Journal of Management in Engineering, 30(1), 1-9. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000168
Enshassi, A., Mohamed, S., Abu Mustafa, Z., & Mayer, P. E. (2007). Factors affecting labour productivity in building projects in the Gaza Strip. Journal of Civil Engineering and Management, 13(4), 245-254.
Enshassi, A., Mohamed, S., Mayer, P., & Abed, K. (2007). Benchmarking masonry labor productivity. International Journal of Productivity and Performance Management, 56(4), 358-368. https://doi.org/10.1108/17410400710745342
Fagbenle, O. I., Ogunde, A. O., & Owolabi, J. D. (2011). Factors affecting the performance of labour in Nigerian construction sites. Mediterranean Journal of Social Sciences, 2(2), 251-257.
Fayek, A. R. (2011). Fuzzy hybrid modeling for strategic construction analysis and delivery. Natural Sciences and Engineering Research Council of Canada Industrial Research Chair proposal, Department of Civil and Environmental. University of Alberta, Edmonton, Alta.
Field, A. (2009). Discovering statistics using SPSS. Thousand Oaks, California, CA.: Sage publications.
Franke, U., Flores, W. R., & Johnson, P. (2009). Enterprise architecture dependency analysis using fault trees and Bayesian networks. In Proceedings of the 42nd Annual Simulation Symposium (ANSS 2009), (pp. 209-216). San Diego, CA: Society for Computer Simulation International
Fulford, R., & Standing, C. (2014). Construction industry productivity and the potential for collaborative practice. International Journal of Project Management, 32(2), 315-326. https://doi.org/10.1016/j.ijproman.2013.05.007
Ghoddousi, P., & Hosseini, M. R. (2012). A survey of the factors affecting the productivity of construction projects in Iran. Technological and Economic Development of Economy, 18(1), 99-116. https://doi.org/10.3846/20294913.2012.661203
Gündüz, U., & Kaya, T. (2017). Regional employment generation potential of the Turkish labor market: An inter-sectoral perspective. Technological and Economic Development of Economy, 23(5), 726-741. https://doi.org/10.3846/20294913.2015.1015110
Hafez, S. M., Aziz, R. F., Morgan, E. S., Abdullah, M. M., & Ahmed, E. K. (2014). Critical factors affecting construction labor productivity in Egypt. American Journal of Civil Engineering, 2(2), 35-40. https://doi.org/10.11648/j.ajce.20140202.14
Hanna, A. S., Taylor, C. S., & Sullivan, K. T. (2005). Impact of extended overtime on construction labor. Journal of Construction Engineering and Management, 131(6), 734-739. https://doi.org/10.1061/(ASCE)0733-9364(2005)131:6(734)
Heravi, G., & Eslamdoost, E. (2015). Applying artificial neural networks for measuring and predicting construction-labor productivity. Journal of Construction Engineering and Management, 141(10), 1-11. https://doi.org/10.1061/(ASCE)0733-9364(2005)131:6(734)
Hickson, B. G., & Ellis, L. A. (2014). Factors affecting construction labour productivity in Trinidad and Tobago. The Journal of the Association of Professional Engineers of Trinidad and Tobago, 42(1), 4-11.
Hiyassat, M. A., Hiyari, M. A., & Sweis, G. J. (2016). Factors affecting construction labour productivity: A case study of Jordan. International Journal of Construction Management, 16(2), 138-149. https://doi.org/10.1080/15623599.2016.1142266
Hoyland, A., & Rausand, M. (2004). System reliability theory models and statistical methods (2nd ed.). Hoboken, New Jersey: John Wiley and Sons.
Hwang, B. G., Zhao, X., & Do, T. H. V. (2014). Influence of trade‐level coordination problems on project productivity. Project Management Journal, 45(5), 5-14. https://doi.org/10.1002/pmj.21445
Iverson, S., Kerkering, J., Coleman, P., & Spokane, W. (2001). Using fault tree analysis to focus mine safety research. In Proceedings of the 108th Annual meeting of the Society for Mining, Metallurgy, and Exploration (pp. 1-10).
Jarkas, A. (2012). Buildability factors influencing concreting labour productivity. Journal of Construction Engineering and Management, 138(1), 89-97. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000404
Jarkas, A. M. (2015). Factors influencing labour productivity in Bahrain’s construction industry. International Journal of Construction Management, 15(1), 94-108. https://doi.org/10.1080/15623599.2015.1012143
Jarkas, A. M., & Bitar, C. G. (2012). Factors affecting construction labour productivity in Kuwait. Journal of Construction Engineering and Management, 138(7), 811-820. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000501
Jarkas, A. M., Al Balushi, R. A., & Raveendranath, P. K. (2015). Determinants of construction labour productivity in Oman. International Journal of Construction Management, 15(4), 332-344. https://doi.org/10.1080/15623599.2015.1094849
Kales, P. (2006). Reliability for technology, engineering and management. Taipei: Pearson Education Taiwan Ltd.
Kaming, P. F., Holt, G. D., Kometa, S. T., & Olomolaiye, P. O. (1998). Severity diagnosis of productivity problems – A reliability analysis. International Journal of Project Management, 16(2), 107-113. https://doi.org/10.1016/S0263-7863(97)00036-7
Karimi, H., Taylor, T. R. B., & Goodrum, P. M. (2017). Analysis of the impact of craft labour availability on North American construction project productivity and schedule performance. Construction Management and Economics, 35(6), 368-380. https://doi.org/10.1080/01446193.2017.1294257
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. https://doi.org/10.1016/j.oceaneng.2015.09.008
Lindhe, A., Rosen, L., Norberg, T., & Bergstedt, O. (2009). Fault tree analysis for integrated and probabilistic risk analysis of drinking water systems. Water Research, 43(6), 1641-1653. https://doi.org/10.1016/j.watres.2008.12.034
Ma, L., Liu, C., & Reed, R. (2017). The impacts of residential construction and property prices on residential construction outputs: An inter-market equilibrium approach. International Journal of Strategic Property Management, 21(3), 296-306. https://doi.org/10.3846/1648715X.2016.1255675
Nasirzadeh, F., & Nojedehi, P. (2013). Dynamic modeling of labor productivity in construction projects. International Journal of Project Management, 31(6), 903-911. https://doi.org/10.1016/j.ijproman.2012.11.003
O’Connor, P. D. T. (2002). Practical reliability engineering. New York: John Wiley & Sons Inc.
Oglesby, C., Parker, H., & Howell, G. (1989). Productivity improvement in construction. New York: McGraw-Hill.
Parchami Jalal, M., & Shoar, S. (2017). A hybrid SD-DEMATEL approach to develop a delay model for construction projects. Engineering, Construction and Architectural Management, 24(4), 629-651. https://doi.org/10.1108/ECAM-02-2016-0056
Robles, G., Stifi, A., Ponz-Tienda, J. L., & Gentes, S. (2014). Labor productivity in the construction industry – Factors influencing the Spanish construction labor productivity. International Journal of Civil and Environmental Engineering, 8(10), 1061-1070.
Shoar, S., & Nazari, A. (2018). An optimization framework for risk response actions selection using hybrid ACO and FTOPSIS. Scientia Iranica (in Press). https://doi.org/10.24200/sci.2018.20225
Shoar, S., Zarandi, H. R., Nasirzadeh, F., & Cheshmikhani, E. (2017). Fast fault tree analysis for hybrid uncertainties using stochastic logic implemented on field‐programmable gate arrays: An application in quantitative assessment and mitigation of welding defects risk. Quality and Reliability Engineering International, 33, 1367-1385. https://doi.org/10.1002/qre.2110
Tanaka, H., Fan, T. L., Lai, F. S., & Toguchi, K. (1983). Fault-tree analysis by fuzzy probability. IEEE Transactions on Reliability, 32(5), 453-457. https://doi.org/10.1109/TR.1983.5221727
Yi, W., & Chan, A. P. C. (2014). Critical review of labor productivity research in construction journals. Journal of Management in Engineering, 30(2), 214-225. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000194
Zadeh, L. (1965). Fuzzy sets. Information and Control, 8(3), 338-353. https://doi.org/10.1016/S0019-9958(65)90241-X
Zhang, L., Skibniewski, M. J., Wu, X., Chen, Y., & Deng, Q. (2014). A probabilistic approach for safety risk analysis in metro construction. Safety Science, 63, 8-17. https://doi.org/10.1016/j.ssci.2013.10.016