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Permanent link (DOI): https://doi.org/10.7939/R3PZ51Z8F

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Ergonomic Risk Assessment in Construction Manufacturing Facilities Open Access

Descriptions

Other title
Subject/Keyword
Ergonomics
Work-related injury
Construction Manufacturing Facility
Muscle fatigue
Physical demand analysis
Surface electromyography
3D visualization
Risk assessment
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Li, Xinming
Supervisor and department
Mustafa Gül (Department of civil and environmental engineering)
Mohamed Al-Hussein (Department of civil and environmental engineering)
Examining committee member and department
Hossein Rouhani (Department of mechanical engineering)
Yasser Mohamed (Department of civil and environmental engineering)
Carl T. Haas (Department of civil and environmental engineering)
Rafiq Ahmad (Department of mechanical engineering)
Department
Department of Civil and Environmental Engineering
Specialization
Construction Engineering and Management
Date accepted
2017-04-03T11:05:02Z
Graduation date
2017-06:Spring 2017
Degree
Doctor of Philosophy
Degree level
Doctoral
Abstract
The construction manufacturing industry in North America has a disproportionately high number of lost-time injuries due to the high physical demand of the labour-intensive tasks it involves. It is essential to investigate the physical demands of body movement in the construction manufacturing workplace in order to proactively identify worker exposure to ergonomic risk. This research thus analyzes the primary ergonomic risk factors that cause work-related injuries: awkward body posture, overexertion, and repetitive motion. This research first develops a framework to approach an improved physical demand analysis for risk identification, evaluation, and mitigation by providing modified work. The framework is implemented in a manufacturing industry facility, and four main ergonomic risk identifications, together with the corresponding modified work, are recommended. Second, a framework of assessing muscle force and muscle fatigue development due to manual repetitive lifting tasks using surface electromyography (sEMG), kinematic motion capture, and human body modelling is also proposed. The results show that sEMG is capable of visualizing muscle activity. However, it is limited to identifying muscle fatigue development of bulkier and superficial muscle bundles in low fat areas. Physiological measurements also have technical, ethical, cost, and real-life implementation limitations. This research thus further investigates an innovative framework for converting observational or video-captured body movements in an actual construction manufacturing plant into 3D modelling for ergonomic risk assessment of continuous motions. The proposed 3D motion-based risk assessment methodology is validated through the aforementioned motion capture experiment to prove the reliability of the framework. The integration between the first and third framework is also proposed and implemented in modular construction operations. Thus the capability of 3D modelling is extended to support the optimization of human body movement and the re-design of the workplace accordingly to mitigate the ergonomic risks inherent in operational tasks. Modified work recommendations are expected as a result of this research, which facilitates the establishment of a more robust return-to-work program for various industries. Ultimately, the goal is to proactively curtail workplace injuries and claims and thereby reduce workers’ compensation insurance costs.
Language
English
DOI
doi:10.7939/R3PZ51Z8F
Rights
This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for the purpose of private, scholarly or scientific research. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
Citation for previous publication
Li, X., Gül, M. and Al-Hussein, M. “A risk assessment framework based on an improved physical demand analysis for the building and manufacturing industries.” International Journal of Industrial Ergonomics (Under review).Li, X., Han, S., Gül, M., Al-Hussein, M. and El-Rich, M. “3D motion-based rapid ergonomic risk assessment framework and its validation method.” Journal of Construction Engineering and Management (Under review).Li, X., Komeili, A., Gül, M., and El-Rich, M. (2017). “A framework for evaluating muscle activity during repetitive manual material handling in construction manufacturing.” Automation in Construction, 79, pp. 39–48.Li, X., Han, S., Gül, M., and Al-Hussein, M. (submitted). “Automated ergonomic risk assessment based on 3D visualization.” Proceedings, 34th International Symposium on Automation and Robotics in Construction, Taibei, Taiwan, June 28-July 1, 2017 (under review).Li, X., Han, S., Gül, M., and Al-Hussein, M. (2016). “3D motion-based ergonomic and body posture analysis in construction.” Proceedings, Modular and Offsite Construction (MOC) Summit, Edmonton, AB, Canada, Sep. 29-Oct. 1, pp. 215–223.Komeili, A., Li, X., Gül, M., Lewicke, J., and El-Rich, M. (2015). “An evaluation method of assessing the low back muscle fatigue in manual material handling.” Proceedings, Modular and Offsite Construction Summit, Edmonton, Alberta, Canada, May 19-21, pp. 467–475.Li, X., Fan, G., Abudan, A., Sukkarieh, M., Inyang, N., Gül, M., El-Rich, M., Al-Hussein, M. (2015). “Ergonomics and physical demand construction manufacturing facility analysis.” Proceedings, 5th International/11th Construction Specialty Conference, Vancouver, British Columbia, Canada, Jun. 8-10.

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