Journal
JOURNAL OF CLEANER PRODUCTION
Volume 120, Issue -, Pages 198-206Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2016.01.070
Keywords
Composite recycling; Resource modelling; Glass fibre reinforced thermoset plastic; Granulator mechanical recycling; Energy demand
Categories
Funding
- UK Engineering and Physical Sciences Research Council (EPSRC) [EP/K026348/1]
- Engineering and Physical Sciences Research Council [EP/K026348/2, EP/K026348/1] Funding Source: researchfish
- EPSRC [EP/K026348/1, EP/K026348/2] Funding Source: UKRI
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Increased demand of fibre reinforced plastic (FRP) composites has led to high volumes of manufacturing scrap and end-of-life waste. Restrictions on landfill disposal and the high energy for virgin material production call for cost effective composite recycling technology. Unfortunately there is limited high integrity environmental related data in literature, to help assess the life cycle benefits of composite recycling, particularly glass fibre reinforced plastic (GFRP). In this work new approaches based on bottom-up unit process modelling were used to model and experimentally validate the energy demand in mechanical recycling of GFRP. Total energy requirement was classified into sources by machine functions (basic energy) and for actual cutting process (tip energy) as modelled from material specific cutting energy for GFRP. The mechanics of cutting was utilised to model the specific energy from orthogonal tests. The model was then extended and validated to cater for mechanical recycling with a milling based granulator recycling machine. Energy demand was modelled and validated for a number of industrial granulators. This paper provides valuable information on the impact of processing rate and granulator capacity in relation to reducing the energy demand in recycling of thermoset based glass fibre (GFRPT). The bottom-up approach is an important framework that can be used to model the energy and environmental footprint of other recycling unit processes. This information provides vital data for life cycle analysis, enabling the assessment of resource hot spots and quantifying the environmental benefits of end-of-life options. (C) 2016 The Authors. Published by Elsevier Ltd.
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