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dc.contributor.authorSanderson, Adam
dc.date.accessioned2019-05-29 17:26:29 (GMT)
dc.date.available2019-05-29 17:26:29 (GMT)
dc.date.issued2019-05-29
dc.date.submitted2019-05-07
dc.identifier.urihttp://hdl.handle.net/10012/14730
dc.description.abstractAs the population and prosperity continue to rise the demand for high-tech products is rapidly increasing. Displays are a huge part of this market with millions being created each year. We have a finite amount of resources on this planet and it is imperative that we properly dispose of our devices. In this thesis an intelligent robotic workcell for dismantling and recycling of flat panel displays is proposed and tested. This system utilizes industrial robots and open source tools to process a flat panel display (FPD) with the goal of removal of cold compact fluorescent tubes (CFLs). These are removed so the FPD can be shredded and properly recycled without the mercury present in the CFLs contaminating the materials or harming workers. This system utilizes many new and innovative techniques including deep learning algorithms for object detection and image segmentation. These deep learning techniques specifically Faster R-CNN for object detection and DeepLab for image segmentation have been shown to be extremely robust and capable in this application. The system was tested both with a real world system and with simulated geometry with a live vision feed. During simulation, the system was capable of processing flat panel FPDs in between 110 and 230 seconds per unit. It has been calculated using the simulation results, that this system can be profitable and has an approximate payback period of between 0.19 and 4.87 years depending on the material being fed into the system. The large range is due to the difference in value between monitor and TV style FPDs. The monitors have far less value than the TVs and are far more difficult to process.en
dc.language.isoenen
dc.publisherUniversity of Waterlooen
dc.subjectrecyclingen
dc.subjectartificial intelligenceen
dc.subjectdeep learningen
dc.subjectroboticsen
dc.subjectneural networken
dc.titleIntelligent Robotic Recycling of Flat Panel Displaysen
dc.typeMaster Thesisen
dc.pendingfalse
uws-etd.degree.departmentMechanical and Mechatronics Engineeringen
uws-etd.degree.disciplineMechanical Engineeringen
uws-etd.degree.grantorUniversity of Waterlooen
uws-etd.degreeMaster of Applied Scienceen
uws.contributor.advisorHamid, Karbasi
uws.contributor.advisorAmir, Khajepour
uws.contributor.affiliation1Faculty of Engineeringen
uws.published.cityWaterlooen
uws.published.countryCanadaen
uws.published.provinceOntarioen
uws.typeOfResourceTexten
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen


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