A methodology for assessing industrial workstations using optical motion capture integrated with digital human models

Abstract

This study examined an existing industrial workstation at an automobile assembly plant using computer aided ergonomics and digital human models. The purpose of this evaluation was the development of a motion capture-based methodology for evaluating workstations to identify potential design issues that could result in musculoskeletal injury in a real work environment. An ergonomic risk assessment was conducted on a sample of operators performing a lifting task manually and using an assist device. An optical motion capture system was setup and calibrated in the industrial workplace to collect motion data. UGS™ JACK digital human modelling software was used for the computer-based ergonomic analysis to evaluate the potential injury risk of the current task, considering difference between using and not using the assist device. The work tasks were decomposed into subtasks before analysis. Muscle activity was also measured by wireless electromyography (EMG) in order to identify physiological indicators of stress and strain. The results suggest although using the assist device decreased injury risk potentially, use of the assist device had an adverse impact on the productivity of the assembly line. Based on the findings of this study, the methodology appears to be appropriate for assessing and predicting potential risks associated with the design of industrial workstations and work tasks. The results also highlight tradeoffs in using an assist device which can decrease injury risk in some cases, while having an adverse impact on the productivity of the assembly line.