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Predicting tool operator capacity to react against torque within acceptable handle deflection limits in automotive
Robert G Radwin1, Amrish Chourasia1, Frank J Fronczak1
1University of Wisconsin-Madison, 1550 Engineering Drive, Madison, WI 53597, USA.
Applied Ergonomics
|February 7, 2016
Summary
A biodynamic model predicted tool handle deflection for auto assembly jobs. Modifications to tool speed and operator position resolved issues in six jobs, ensuring operator capacity.
Area of Science:
- Ergonomics and Human Factors
- Occupational Health and Safety
- Mechanical Engineering
Background:
- Threaded fastener tools are prevalent in auto assembly.
- Assessing tool handle deflection is crucial for operator safety and comfort.
- Existing psychophysical limits for tool handle deflection require validation through biodynamic modeling.
Purpose of the Study:
- To predict the proportion of tool operators capable of maintaining established threaded fastener tool handle deflection limits.
- To identify specific tool, task, and workstation parameters influencing tool handle deflection.
- To evaluate the effectiveness of a biodynamic tool operator model in identifying and resolving stressful tool installations.
Main Methods:
- A biodynamic tool operator model was developed and utilized.
- Parameters including tool geometry, speed, torque, mass moments of inertia, fastener torque, joint properties, and workstation distances were collected.
- Tool mass moments of inertia were measured using a novel rotating system device.
- Handle deflection was predicted for 35 tools across 69 installations in an auto assembly plant.
Main Results:
- Handle deflection exceeded established limits for six out of 69 evaluated jobs.
- The biodynamic model accurately predicted these exceedances.
- Modifications in tool speed and operator positioning successfully brought the problematic jobs within acceptable deflection limits, as predicted by the model.
Conclusions:
- Biodynamic tool operator models are effective tools for identifying stressful tool installations.
- These models can predict the efficacy of interventions aimed at improving ergonomic conditions.
- The study highlights the importance of considering tool, task, and workstation interactions in ensuring operator capacity and safety.
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