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With the advance of human-robot collaboration (HRC), collaborative robots (cobots) have emerged as solutions to alleviate the manual tasks involved in electronic waste (e-waste) disassembly. This study employed surface electromyography (EMG) to investigate whether cobots can enhance muscle coordination. EMG-EMG coherence in both beta and gamma bands was calculated from 22 participants to quantify coordination between four muscle groups—biceps brachii (BB), brachioradialis (BR), upper trapezius (UT), and erector spinae (ES). Comparison results showed that after the introduction of the cobot, significant increases in left BR&BB, BR&UT, BR&ES, and BB&UT pairs, right BR&BB, BR&UT, and BB&ES pairs, and bilateral BR pair were observed. Notably, left BR&ES presented the most substantial increase at 18.88% and 26.39% in the beta and gamma bands, respectively ( p < .05). These findings suggest that cobots hold potential to enhance muscle coordination during e-waste disassembly, thereby shedding light on the construction of HRC-based e-waste disassembly systems.
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Human Workload and Ergonomics during Human-Robot Collaborative Electronic Waste Disassembly
A rapid rise in the recycling and remanufacturing of end-of-use electronic waste (e-waste) has been observed due to multiple factors including our increased dependence on electronic products and the lack of resources to meet the demand. E-waste disassembly, which is the operation of extracting valuable components for recycling purposes, has received ever increasing attention as it can serve both the economy and the environment. Traditionally, e-waste disassembly is labor intensive with significant occupational hazards. To reduce labor costs and enhance working efficiency, collaborative robots (cobots) might be a viable option and the feasibility of deploying cobots in high-risk or low value-added e-waste disassembly operations is of tremendous significance to be investigated. Therefore, the major objective of this study was to evaluate the effects of working with a cobot during e-waste disassembly processes on human workload and ergonomics through a human subject experiment. Statistical results revealed that using a cobot to assist participants with the desktop disassembly task reduced the sum of the NASA-TLX scores significantly compared to disassembling by themselves (p = 0.001). With regard to ergonomics, a significant reduction was observed in participants’ mean L5/S1 flexion angle as well as mean shoulder flexion angle on both sides when working with the cobot (p < 0.001). However, participants took a significantly longer time to accomplish the disassembly task when working with the cobot (p < 0.001), indicating a trade-off of deploying cobot in the e-waste disassembly process. Results from this study could advance the knowledge of how human workers would behave and react during human-robot collaborative e-waste disassembly tasks and shed light on the design of better HRC for this specific context.
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- Award ID(s):
- 2026276
- PAR ID:
- 10465131
- Date Published:
- Journal Name:
- 2022 IEEE 3rd International Conference on Human-Machine Systems (ICHMS)
- Page Range / eLocation ID:
- 1 to 6
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ICHMS56717.2022.9980828
