Machine Learning in Manufacturing Ergonomics: Recent Advances, Challenges, and Opportunities

Sujee Lee, Li Liu, Robert Radwin, Jingshan Li
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/g32gcto57vduveq2eb7bes5y7a" style="color: black;">IEEE Robotics and Automation Letters</a> </i> &nbsp;
The rapid development of machine learning (ML) technology has introduced substantial impact on ergonomics research in manufacturing. Numerous studies and practices have been carried out to apply ML techniques to address manufacturing ergonomics issues, which has brought extensive opportunities as well as significant challenges. To incentivize future research in this area, this letter reviews the recent advances of ML applications in manufacturing ergonomics, and discusses future research
more &raquo; ... nities and challenges from ML, ergonomics, and manufacturing systems perspectives.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/lra.2021.3084881">doi:10.1109/lra.2021.3084881</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/hqdsvn3v7vcepfv5orvqlp57lu">fatcat:hqdsvn3v7vcepfv5orvqlp57lu</a> </span>
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