Prediction of Ergonomic Risks and Impacts on Construction Schedule through Agent-Based Simulation
Publication: Journal of Construction Engineering and Management
Volume 149, Issue 3
Abstract
Construction workers are vulnerable to excessive workloads that may cause ergonomic risks, disturbing the construction schedule. Hence, ergonomic risks and the responding measures for mitigating them, namely ergonomic measures, need to be predicted and assessed so as to help make decisions about management policies. This study focuses on agent-based simulation to predict ergonomic risks and impacts of ergonomic measures on the construction schedule (ERIEMCS) along with the construction process consisting of physical or light tasks. Workers are regarded as the agents and their behaviors in performing tasks and ergonomic measures are modeled by considering different physical capacities due to different workers’ ages. Energy expenditure–based fatigue quantification and the Ovako working posture analyzing system (OWAS) –based quantification of work-related musculoskeletal disorder (WMSD) risk for an individual worker are the basis for quantitative prediction of the fatigue and the WMSD risks of a crew undertaking the construction process through agent-based simulation. An application study based on a prefabricated construction project is presented to demonstrate and justify the proposed method. The results indicate that ergonomic risks can be effectively reduced by adopting ergonomic measures to balance mitigating such risks and maintaining productivity. Prediction of the ERIEMCS through agent-based simulation prior to commencement of work facilitates investigating the effects of aging workers and planning their working schedules using ergonomic measures in combination with schedule management. This study contributes to the body of knowledge on simulation-based methodology for applying ergonomics in construction management, which is especially meaningful given the trend of labor aging and the direction of industrialization in construction.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some data used in this study are available from the corresponding author upon reasonable request, while some parts of the data used in this study cannot be shared at this time as they also form the part of an ongoing study.
Acknowledgments
This study is supported by the National Natural Science Foundation of China (Project No. 71972167) and the Pioneer and Leading Goose R&D Program of Zhejiang (Project No. 2022C01130).
References
Abdelhamid, T. S., and J. G. Everett. 2002. “Physiological demands during construction work.” J. Constr. Eng. Manage. 128 (5): 427–437. https://doi.org/10.1061/(ASCE)0733-9364(2002)128:5(427).
Alzraiee, H., T. Zayed, and O. Moselhi. 2015. “Dynamic planning of construction activities using hybrid simulation.” Autom. Constr. 49 (Jan): 176–192. https://doi.org/10.1016/j.autcon.2014.08.011.
Antwi-Afari, M. F., H. Li, Y. Yu, and L. Kong. 2018. “Wearable insole pressure system for automated detection and classification of awkward working postures in construction workers.” Autom. Constr. 96 (Dec): 433–441. https://doi.org/10.1016/j.autcon.2018.10.004.
Berti, N., S. Finco, O. Battaïa, and X. Delorme. 2021. “Ageing workforce effects in dual-resource constrained job-shop scheduling.” Int. J. Prod. Econ. 237 (Jul): 108151. https://doi.org/10.1016/j.ijpe.2021.108151.
Binhomaid, O., and T. Hegazy. 2020. “Agent-based simulation of workers’ behaviors, productivity, and safety around construction obstacles.” Can. J. Civ. Eng. 48 (8): 969–978. https://doi.org/10.1139/cjce-2019-0320.
Choi, B., and S. Lee. 2018. “An empirically based agent-based model of the sociocognitive process of construction workers’ safety behavior.” J. Constr. Eng. Manage. 144 (2): 4017102. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001421.
Garg, A., D. B. Chaffin, and G. D. Herrin. 1978. “Prediction of metabolic rates for manual materials handling jobs.” Am. Ind. Hyg. Assoc. J. 39 (8): 661–674. https://doi.org/10.1080/0002889778507831.
Golabchi, A., S. Han, and S. AbouRizk. 2018. “A simulation and visualization-based framework of labor efficiency and safety analysis for prevention through design and planning.” Autom. Constr. 96 (Dec): 310–323. https://doi.org/10.1016/j.autcon.2018.10.001.
Golabchi, A., S. Han, J. Seo, S. Han, S. Lee, and M. Al-Hussein. 2015. “An automated biomechanical simulation approach to ergonomic job analysis for workplace design.” J. Constr. Eng. Manage. 141 (8): 4015020. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000998.
Hajdu, M., and O. Bokor. 2016. “Sensitivity analysis in PERT networks: Does activity duration distribution matter?” Autom. Constr. 65 (May): 1–8. https://doi.org/10.1016/j.autcon.2016.01.003.
Hignett, S., and L. McAtamney. 2000. “Rapid entire body assessment (REBA).” Appl. Ergon. 31 (2): 201–205. https://doi.org/10.1016/S0003-6870(99)00039-3.
Inyang, N., M. Al-Hussein, M. El-Rich, and S. Al-Jibouri. 2012. “Ergonomic analysis and the need for its integration for planning and assessing construction tasks.” J. Constr. Eng. Manage. 138 (12): 1370–1376. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000556.
Jebelli, H., J. Seo, S. Hwang, and S. Lee. 2020. “Physiology-based dynamic muscle fatigue model for upper limbs during construction tasks.” Int. J. Ind. Ergon. 78 (Jul): 102984. https://doi.org/10.1016/j.ergon.2020.102984.
Jin, R., H. Zhang, D. Liu, and X. Yan. 2020. “IoT-based detecting, locating and alarming of unauthorized intrusion on construction sites.” Autom. Constr. 118 (Oct): 103278. https://doi.org/10.1016/j.autcon.2020.103278.
Kang, D., J.-H. Woo, and Y.-C. Shin. 2007. “Distribution and determinants of maximal physical work capacity of Korean male metal workers.” Ergonomics 50 (12): 2137–2147. https://doi.org/10.1080/00140130701450153.
Karhu, O., P. Kansi, and I. Kuorinka. 1977. “Correcting working postures in industry: A practical method for analysis.” Appl. Ergon. 8 (4): 199–201. https://doi.org/10.1016/0003-6870(77)90164-8.
Kazil, J., D. Masad, and A. Crooks. 2020. “Utilizing Python for agent-based modeling: The MESA framework.” In Proc., SBP-BRiMS 2020, 308–317. Cham, Switzerland: Springer. https://link.springer.com/chapter/10.1007/978-3-030-61255-9_30.
Kenny, G. P., H. Groeller, R. McGinn, and A. D. Flouris. 2016. “Age, human performance, and physical employment standards.” Supplement, Appl. Physiol. Nutr. Metab. 41 (S2): S92–S107. https://doi.org/10.1139/apnm-2015-0483.
Kenny, G. P., J. E. Yardley, L. Martineau, and O. Jay. 2008. “Physical work capacity in older adults: Implications for the aging worker.” Am. J. Ind. Med. 51 (8): 610–625. https://doi.org/10.1002/ajim.20600.
Khodabandelu, A., and J. Park. 2021. “Agent-based modeling and simulation in construction.” Autom. Constr. 131 (Nov): 103882. https://doi.org/10.1016/j.autcon.2021.103882.
Koc, K., Ö. Ekmekcioğlou, and A. P. Gurgun. 2021. “Integrating feature engineering, genetic algorithm and tree-based machine learning methods to predict the post-accident disability status of construction workers.” Autom. Constr. 131 (Nov): 103896. https://doi.org/10.1016/j.autcon.2021.103896.
Kong, L., H. Li, Y. Yu, H. Luo, M. Skitmore, and A.-A. M. Fordjour. 2018. “Quantifying the physical intensity of construction workers, a mechanical energy approach.” Adv. Eng. Inf. 38 (Oct): 404–419. https://doi.org/10.1016/j.aei.2018.08.005.
Lee, T.-H., and C.-S. Han. 2013. “Analysis of working postures at a construction site using the OWAS method.” Int. J. Occup. Saf. Ergon. 19 (2): 245–250. https://doi.org/10.1080/10803548.2013.11076983.
Lu, M., C. M. Cheung, H. Li, and S.-C. Hsu. 2016. “Understanding the relationship between safety investment and safety performance of construction projects through agent-based modeling.” Accid. Anal. Prev. 94 (Sep): 8–17. https://doi.org/10.1016/j.aap.2016.05.014.
McAtamney, L., and E. N. Corlett. 1993. “RULA: A survey method for the investigation of work-related upper limb disorders.” Appl. Ergon. 24 (2): 91–99. https://doi.org/10.1016/0003-6870(93)90080-S.
National Bureau of Statistics of China. 2019. “National report on migrant worker monitoring and survey 2019.” Accessed April 30, 2020. http://www.stats.gov.cn/tjsj/zxfb/202004/t20200430_1742724.html.
Peng, L., and A. H. S. Chan. 2020. “Adjusting work conditions to meet the declined health and functional capacity of older construction workers in Hong Kong.” Saf. Sci. 127 (Jul): 104711. https://doi.org/10.1016/j.ssci.2020.104711.
Polat, G., D. Arditi, and U. Mungen. 2007. “Simulation-based decision support system for economical supply chain management of rebar.” J. Constr. Eng. Manage. 133 (1): 29–39. https://doi.org/10.1061/(ASCE)0733-9364(2007)133:1(29).
Price, A. D. F. 1990. “Calculating relaxation allowances for construction operatives—Part 1: Metabolic cost.” Appl. Ergon. 21 (4): 311–317. https://doi.org/10.1016/0003-6870(90)90202-9.
Rand, W., and R. T. Rust. 2011. “Agent-based modeling in marketing: Guidelines for rigor.” Int. J. Res. Marketing 28 (3): 181–193. https://doi.org/10.1016/j.ijresmar.2011.04.002.
Seo, J., S. Lee, and J. Seo. 2016. “Simulation-based assessment of workers’ muscle fatigue and its impact on construction operations.” J. Constr. Eng. Manage. 142 (11): 4016063. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001182.
Shewchuk, J. P., M. A. Nussbaum, S. Kim, and S. Sarkar. 2017. “Simulation modeling and ergonomic assessment of complex multiworker physical processes.” IEEE Trans. Hum.-Mach. Syst. 47 (6): 777–788. https://doi.org/10.1109/THMS.2016.2628771.
Sukumaran, P., M. E. Bayraktar, T. Hong, and M. Hastak. 2006. “Model for analysis of factors affecting construction schedule in highway work zones.” J. Transp. Eng. 132 (6): 508–517. https://doi.org/10.1061/(ASCE)0733-947X(2006)132:6(508).
Umer, W., H. Li, G. P. Y. Szeto, and A. Y. L. Wong. 2017. “Identification of biomechanical risk factors for the development of lower-back disorders during manual rebar tying.” J. Constr. Eng. Manage. 143 (1): 04016080. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001208.
Umer, W., H. Li, Y. Yu, M. F. Antwi-Afari, S. Anwer, and X. Luo. 2020. “Physical exertion modeling for construction tasks using combined cardiorespiratory and thermoregulatory measures.” Autom. Constr. 112 (Apr): 103079. https://doi.org/10.1016/j.autcon.2020.103079.
University of Michigan Center for Ergonomics. 2020. “3D static strength prediction program (3DSSPP).” Accessed June 7, 2022. https://c4e.engin.umich.edu/tools-services/3dsspp-software/.
Wang, D., F. Dai, and X. Ning. 2015. “Risk assessment of work-related musculoskeletal disorders in construction: State-of-the-art review.” J. Constr. Eng. Manage. 141 (6): 04015008. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000979.
Watkins, M., A. Mukherjee, N. Onder, and K. Mattila. 2009. “Using agent-based modeling to study construction labor productivity as an emergent property of individual and crew interactions.” J. Constr. Eng. Manage. 135 (7): 657–667. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000022.
Wong, F. K.-W., Y.-H. Chiang, F. A. Abidoye, and S. Liang. 2019. “Interrelation between human factor–related accidents and work patterns in construction industry.” J. Constr. Eng. Manage. 145 (5): 04019021. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001642.
Yan, X., H. Li, A. R. Li, and H. Zhang. 2017a. “Wearable IMU-based real-time motion warning system for construction workers’ musculoskeletal disorders prevention.” Autom. Constr. 74 (Feb): 2–11. https://doi.org/10.1016/j.autcon.2016.11.007.
Yan, X., H. Li, C. Wang, J. Seo, H. Zhang, and H. Wang. 2017b. “Development of ergonomic posture recognition technique based on 2D ordinary camera for construction hazard prevention through view-invariant features in 2D skeleton motion.” Adv. Eng. Inf. 34 (Oct): 152–163. https://doi.org/10.1016/j.aei.2017.11.001.
Yan, X., H. Zhang, and W. Zhang. 2022. “Intelligent monitoring and evaluation for the prefabricated construction schedule.” Comput.-Aided Civ. Infrastruct. Eng. 1–17. https://doi.org/10.1111/mice.12838.
Yang, J.-B., and C.-K. Kao. 2012. “Critical path effect based delay analysis method for construction projects.” Int. J. Project Manage. 30 (3): 385–397. https://doi.org/10.1016/j.ijproman.2011.06.003.
Yu, Y., H. Li, X. Yang, L. Kong, X. Luo, and A. Y. L. Wong. 2019. “An automatic and non-invasive physical fatigue assessment method for construction workers.” Autom. Constr. 103 (Jul): 1–12. https://doi.org/10.1016/j.autcon.2019.02.020.
Zhang, P., N. Li, Z. Jiang, D. Fang, and C. J. Anumba. 2019. “An agent-based modeling approach for understanding the effect of worker-management interactions on construction workers’ safety-related behaviors.” Autom. Constr. 97 (Jan): 29–43. https://doi.org/10.1016/j.autcon.2018.10.015.
Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 149 • Issue 3 • March 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Feb 23, 2022
Accepted: Aug 29, 2022
Published online: Dec 24, 2022
Published in print: Mar 1, 2023
Discussion open until: May 24, 2023
ASCE Technical Topics:
- Business management
- Construction engineering
- Construction management
- Construction methods
- Disaster risk management
- Employment
- Fatigue (material)
- Labor
- Management methods
- Material mechanics
- Material properties
- Materials engineering
- Mitigation and remediation
- Personnel management
- Practice and Profession
- Risk management
- Scheduling
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.