Polymers are ubiquitous in modern manufactured products. The potential detrimental impacts of their end-of-life disposal have stimulated significant increases in recycling rates. Recyclate purity is paramount; however this must be achieved with a positive net energy balance. Existing technologies for identification and separation of polymers are often both expensive and energy intensive. This paper investigates Infrared (IR) imaging to extract information on thermal properties of various product polymers within a recycling line. An intelligent decision making support system is enabled using neural network based pattern recognition for automatic polymer identification and classification. Potential energy savings versus current technologies are discussed.
Funding
This work was funded by the Engineering and Physical Sciences Research Council [grant number EP/I033351/1] as part of the Centre for Innovative Manufacturing in Industrial Sustainability.
History
School
Mechanical, Electrical and Manufacturing Engineering
Published in
10th CIRP Conference on Intelligent Computation in Manufacturing Engineering - CIRP ICME '16
Citation
COLWILL, J. ... et al, 2016. Energy-efficient systems for the sensing and separation of mixed polymers. Procedia CIRP, 62, pp.512-517.
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/
Acceptance date
2016-06-08
Publication date
2016
Notes
This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/ ) This paper was presented at the 10th CIRP Conference on Intelligent Computation in Manufacturing Engineering - CIRP ICME '16, Naples.