Advanced wearable inertial tracking system to monitor automotive assembly operator motion for human simulation applications

Capturing the real human motions on the assembly plant floor is the key point for developing accurate virtual simulations. The real human motions of specific workstation operations at Ford Oakville Assembly Plant by using wearable inertial sensors will be collected. After data collection, virtual simulations will be performed for all the recorded operation tasks. Based on simulations, physicians can observe and conduct ergonomic assessment of each of operation tasks on the plant floor. In addition, developing an accurate posture prediction algorithm is important for the future assembly operation designs. This project will focus on the development of this new algorithm for some specific operation tasks. Once this developed posture prediction algorithm is validated, it will enable engineers to design assembly operations which do not exist at the moment. The real-time ergonomic analyses will aid engineers in assessing injury risks in the assembly design process.

Intern: 
Adrian de Gouw
Xiaoxu Ji
Faculty Supervisor: 
Joel Cort
Province: 
Ontario
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