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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/21821

Title: Energy-efficient systems for the sensing and separation of mixed polymers
Authors: Simeone, Alessandro
Colwill, James
Gould, Oliver
Woolley, Elliot
Mulvenna, Ciaran
Keywords: Polymers
Pattern recognition
Recycling
Issue Date: 2016
Publisher: Elsevier / © The Authors.
Citation: SIMEONE, A. ... et al, 2016. Energy-efficient systems for the sensing and separation of mixed polymers. Procedia CIRP, forthcoming.
Abstract: 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.
Description: This paper is closed access until online publication. It was presented at the 10th CIRP Conference on Intelligent Computation in Manufacturing Engineering - CIRP ICME '16, Naples.
Sponsor: 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.
Version: Published
URI: https://dspace.lboro.ac.uk/2134/21821
Publisher Link: http://www.sciencedirect.com/science/journal/22128271
ISSN: 2212-8271
Appears in Collections:Closed Access (Mechanical, Electrical and Manufacturing Engineering)

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