Cyber-physical systems in the re-use, refurbishment and recycling of used electrical and electronic equipment
journal contributionposted on 22.09.2017 by Richard Sharpe, Paul Goodall, Aaron Neal, Paul Conway, Andrew West
Any type of content formally published in an academic journal, usually following a peer-review process.
The aim of the research outlined in this paper is to demonstrate the implementation of a Cyber-Physical System (CPS) within the End of Life (EoL) processing of Electrical and Electronic Equipment (EEE). The described system was created by reviewing related areas of research, capturing stakeholder’s requirements, designing system components and then implementing within an actual EoL EEE processer. The research presented in this paper details user requirements, relevant to any EoL EEE processer, and provides information of the challenges and benefits of utilising CPSs systems within this domain. The system implemented allowed an EoL processer to attach passive Ultra High Frequency (UHF) Radio Frequency Identification (RFID) tags to cores (i.e. mobile phones and other IT assets) upon entry to the facility allowing monitoring and control of the core’s refurbishment. The CPS deployed supported the processing and monitoring requirements of PAS 141:2011, a standard for the correct refurbishment of both used and waste EEE for reuse. The implemented system controls how an operator can process a core, informing them which process or processes should be followed based upon the quality of the core, the recorded results of previous testing and any repair efforts. The system provides Human-Computer Interfaces (HCIs) to aid the user in recording core and process information which is then used to make decisions on the additional processes required. This research has contributed to the knowledge of the advantages and challenges of CPS development, specifically within the EoL domain, and documents future research goals to aid EoL processing through more advanced decision support on a core’s processes.
This work was supported by Innovate UK for the funding of project “INTELLICO” and EPSRC for the project “AIIM” [grant reference EP/K014137/1].
- Mechanical, Electrical and Manufacturing Engineering