Primary Areas of Interest
Research at Occupational Ergonomics Research Lab seeks improvements in industrialized construction by evaluating ergonomic risks and investigating corresponding corrective measures to secure the health and safety of workers and enhance workplace productivity.
Automated proactive 3D fuzzy ergonomic analysis for rapid workplace design and modification
Although advanced technologies are used in many construction industries, physical operations are still essential. These physical operations are strongly affected by workplace design. Ergonomic-centric workplace design may enhance the quality and productivity in the industry, while workplaces with inherently poor ergonomic design may lead to work-related musculoskeletal disorders (WMSDs) for workers, resulting in an increase in compensation costs and schedule overruns due to work absenteeism. Reliable analysis that identifies and evaluates the ergonomic risks of physical operations from the perspective of workplace design, leads not only to enhanced occupational health practices, but also improved overall project quality and productivity.
VR applied for ergonomic risk assessment of industrialized construction tasks
To reduce worker exposure to the physical demands associated with work-related musculoskeletal disorders, investigation of workstation design is needed in the industrialized construction industry. Virtual reality (VR) is emerging as an effective alternative to simulate human body motions in a controlled environment and overcome challenges encountered in traditional prototyping methods such as physical mock-ups. This research proposes a VR-based ergonomic assessment method to evaluate worker body posture during manual handling operational tasks in industrialized construction. To develop, demonstrate, and verify the accuracy of the proposed method, a VR application for data collection is developed in two phases: (1) a pilot test with 4 participants, followed by (2) validated experiment with 13 participants. In the second round of experiments, participant background information and feedback on the developed VR application is obtained through an online questionnaire, while information on participant body motion is collected using video recording and evaluated using an existing ergonomic risk assessment method, Rapid Upper Limb Assessment (RULA). Ergonomic risks are identified and classified accordingly, with an accuracy of approximately 82% achieved from the RULA scores calculated in the physical mock-up and the designed VR application. Based on the results obtained, it is concluded that the proposed VR-based ergonomic risk assessment methodology is suitable for performing ergonomic analysis of manual handling operational tasks similar to the one investigated in this study.
An improved Physical Demand Analysis Framework based on Ergonomic Risk Assessment Tools for the Manufacturing Industry
Most of the operational tasks in the manufacturing process entail extensive physical involvement despite the introduction of automated equipment. Due to the high physical demand in manufacturing, the need for proactive risk assessment to decrease potential injury cannot be ignored. Physical Demand Analysis (PDA) is a widely used tool recommended to all manufacturers by the Canadian Workers’ Compensation Board to document the physical, cognitive, and environmental demands of essential tasks. However, limitations exist in utilizing the content generated in current PDA practice to conduct risk identification and risk assessment, and it has limited functionality for providing modified work to proactively mitigate risk. This research summarizes the input requirements of risk assessment tools and proposes an improved PDA form with an integrated framework to facilitate the comprehensive and intelligent use of PDA. This research focuses on three aspects of PDA implementation—risk identification, risk evaluation, and risk mitigation—targeting the development of modified work for the manufacturing industry. The framework is implemented in a window and door manufacturing facility, and a case study of a window glazing station is investigated. Based on the findings of the research, four main ergonomic risk assessments and identifications are recommended.
A framework for evaluating muscle activity during repetitive manual
material handling in construction manufacturing
Workers in construction sites are exposed to highly labor-intensive tasks. Ergonomic principles, in addition to engineering considerations, should thus be included in the design of workstations in order to minimize the risk of injury. The objective of this paper is to propose a framework to assess muscle force and muscle fatigue development due to manual lifting tasks using surface electromyography (sEMG) and human body modelling. Muscle forces are calculated using the human body model and compared qualitatively to sEMG muscle activities. The results show that sEMG is capable of visualizing muscle activity. However, sEMG application in identifying muscle fatigue development is limited to bulkier and superficial muscle bundles in low fat areas. The proposed human body model, which is driven by kinematic motion capture data, predicts muscle forces during the entire task maneuver. The predicted muscle forces from the human body model are compared with sEMG data from corresponding muscles as well as data available in the literature. In future research, the developed model will be used to determine optimal task maneuvers that minimize muscle forces with the ultimate goal of preventing muscle injuries in workstations.
Automated post-3D visualization ergonomic analysis system for rapid
workplace design in modular construction
Conventional risk assessment of physical work methods is time-consuming and requires human subjects to perform the operational task; 3D visualization, alternatively, allows users to simulate the task, which is less time consuming and eliminates the need for costly onsite devices and the detrimental effect of human error during experimentation. This paper presents the development of an automated post-3D visualization ErgoSystem, a system that automates ergonomic risk assessment based on 3D modelling with the support of user-friendly platform for rapid workplace design. Rapid Entire Body Assessment and Rapid Upper Limb Assessment have also been integrated and adjusted into the proposed system. The system is implemented into the process of comparing various methods of placing insulation onto a modularized panel to demonstrate how the change of movements correlates to the change of workplace design. The objective is to proactively mitigate ergonomic risk at the workplace and to reduce injuries and workers' compensation costs.
3D Visualization-Based Ergonomic Risk Assessment and Work Modification Framework and
Its Validation for a Lifting Task
The construction manufacturing industry in North America has a disproportionately high number of lost-time injuries because of the high physical demand of the labor-intensive tasks it involves. It is thus essential to investigate the physical demands of body movement in the construction manufacturing workplace to proactively identify worker exposure to ergonomic risk. This paper proposes a methodology to use three-dimensional (3D) skeletal modeling to imitate human body movement in an actual construction manufacturing plant for ergonomic risk assessment of a workstation. The inputs for the creation of an accurate and reliable 3D model are also identified. Through 3D modeling, continuous human body motion data can be obtained (such as joint coordinates and joint angles) for risk assessment analysis using existing risk assessment algorithms. The presented framework enables risk evaluation by detecting awkward body postures and evaluating the handled force/load and frequency that cause ergonomic risks during manufacturing operations. The results of the analysis are expected to facilitate the development of modified work to the workstation, which will potentially reduce injuries and workers’ compensation insurance costs in the long term for construction manufacturers. The proposed framework can also be expanded to evaluate workstations in the design phase without the need for physical imitation by human subjects. In this paper, the proposed 3D visualization-based ergonomic risk assessment methodology is validated through an optical marker-based motion capture experiment for a lifting task in order to prove the feasibility and reliability of the framework. It is also compared to the traditional manual observation method. Three subjects are selected to conduct the experiment and three levels of comparison are completed: joint angles comparison, risk rating comparison for body segments, and Rapid Entire Body Assessment/Rapid Upper Limb Assessment (REBA/RULA) total risk rating and risk level comparison.
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