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Optimising industrial food waste management
journal contribution
posted on 2017-01-19, 15:41 authored by Guillermo Garcia-Garcia, Elliot WoolleyElliot Woolley, Shahin RahimifardShahin RahimifardGlobal levels of food waste are attracting growing concern and require immediate action to mitigate their negative ecological and socio-economic ramifications. In the developed world, of the order of 20-40% of food waste is generated at the manufacturing stage of supply chains and is often managed in non-optimised ways leading to additional environmental impacts. This research
describes a novel decision-support tool to enable food manufacturers to evaluate a range of waste management options and
identify the most sustainable solution. A nine-stage qualitative evaluation tool is used in conjunction with a number of
quantitative parameters to assess industrial food waste, which is then used to generate performance factors that enable the evaluation of economic, environmental and social implications of a range of food-waste management alternatives. The applicability of this process in a software-based decision-support tool is discussed in the context of two industrial case studies.
Funding
This research is funded by the Engineering and Physical Sciences Research Council (EPSRC) UK through the grant EP/K030957/1.
History
School
- Mechanical, Electrical and Manufacturing Engineering
Published in
14th Global Conference on Sustainable ManufacturingCitation
GARCIA-GARCIA, G., WOOLLEY, E. and RAHIMIFARD, S., 2017. Optimising industrial food waste management. Procedia Manufacturing, 8, pp. 432-439.Publisher
Elsevier © The AuthorsVersion
- VoR (Version of Record)
Publisher statement
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
2016-09-11Publication date
2017Notes
This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International licence (CC BY-NC-ND). Full details of this licence are available at: http://creativecomons.org/licenses/by-nc-nd/4.0. This paper was also presented at the 14th Global Conference on Sustainable Manufacturing (GCSM), Stellenbosch, South Africa, 3rd-5th October 2016.ISSN
2351-9789Publisher version
Language
- en