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Access Type
WSU Access
Date of Award
January 2024
Degree Type
Dissertation
Degree Name
Ph.D.
Department
Industrial and Manufacturing Engineering
First Advisor
Jeremy L. Rickli
Abstract
The increased interest in scarce raw materials for new technologies, such as batteries and electric motors, has created a risk to their supplier. Rapid demand intensification can lead to supplier disruption and damage national economies. Oppositely, enhancing these materials' reverse cycles (i.e., recycling, repair, and remanufacturing) into the product lifecycle is fundamental to mitigate supply disruptions, a strategy defined under the Circular Economy philosophy. As the primary step, disassembly plays a critical role in material recovery and still needs advancement from Industry and Academia. Motivated by the recent introduction of sensing technologies allowing humans and robots to work safely in a shared workspace, this investigation aims to handle the automation gap in the recovery industries through human engagement in the robotic processes.Aiming to leverage high-volume disassembly lines, this investigation develops a systematic procedure for disassembly task recognition and disassembly sequence planning through human-robot interaction. Two primitive disassembly tasks are modeled and used to label collaborative robots (cobot) programs, which are used to output multiple robot trajectories. The human interaction in hand-guiding the cobot during the disassembly program is studied to improve the accuracy of the cobot's positioning and disassembly of components. In addition, the impact of the product orientation on the physical workspace on disassembly sequence generation is studied and compared to CAD-simulated disassembly sequences. The disassembly framework has demonstrated practical potential in extracting disassembly information (e.g., disassembly tasks and sequence) from human-cobot interactions. This enhances the setup capabilities of other robots in both virtual and physical disassembly experiments. However, physical disassembly trials have indicated a need for a more robust trajectory prediction when improving the accuracy of hand-guided programs. In addition, the CAD-based disassembly sequence generation methodology has been tested over 1500 CAD models, showing great potential in use for disassembly sequence planning, and demonstrated how to modify the Interference Matrix to simulate the physical disassembly sequence space.
Recommended Citation
Jacomini Prioli, Joao Paulo, "A Cyber-Physical System Approach For Collaborative Disassembly Automation" (2024). Wayne State University Dissertations. 4075.
https://digitalcommons.wayne.edu/oa_dissertations/4075