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 methodology useful 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 lifting task while being performed both manually and using an assist device. JACK digital human modeling and ergonomics software were used to conduct a computer-based ergonomic analysis. Four analysis tools in JACK (static strength analysis, rapid upper limb assessment, metabolic energy expenditure analysis and NIOSH lift analysis) were used to evaluate the potential injury risk of the current method of task performance and there is any difference between using and not using the assist device. Muscle activity was measured by electromyography (EMG) to identify physiological indicators of fatigue. Also, Borg¡¯s Rate of Perceived Exertion (RPE) scale was administered to obtain psychophysical data. Results of this study revealed that there were relative stresses on the trunk and arm areas when the task was performed manually. The results also 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 used appears to be an appropriate ergonomic analysis tool for assessing and predicting potential risks associated with the design of industrial workstations. Furthermore this methodology can be extended to designing and redesigning industrial workstations.
| Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-5309 |
| Date | 10 December 2005 |
| Creators | Du, Jinyan |
| Publisher | Scholars Junction |
| Source Sets | Mississippi State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
Page generated in 0.0017 seconds