Identification and analysis of attributes for industrial food waste management modelling
journal contributionposted on 26.04.2019, 10:49 by Guillermo Garcia-Garcia, Elliot WoolleyElliot Woolley, Shahin RahimifardShahin Rahimifard
Due to the large quantities of food waste generated by manufacturers and the associated environmental impact of these waste streams, improving food waste management is vital for achieving a more sustainable food system. Management of food waste can be complex and the most appropriate methods may not always be selected. There are a range of aspects to consider in order to select the most sustainable option to manage food waste, such as the specific type of food waste generated, waste management options available, characteristics of food companies that generate food waste, features of the waste management processors that will manage it, and the sustainability implications of dealing with the food waste. To support food waste management decision making, this paper presents a modelling procedure to assist in identifying what type and range of information is needed to model food waste management systems, allowing the user to follow a systematic methodology to make more informed decisions. This procedure is based on the identification and analysis of qualitative and quantitative attributes necessary to model food waste management and an assessment of their relationships. Specifically, it describes a process to ensure that all relevant attributes are considered during the decision-making process. A case study with a large UK food and drink manufacturer is used to demonstrate the applicability and usefulness of this procedure. In conclusion, the systematic procedure presented in this paper provides a methodology to identify opportunities to improve the sustainability of industrial food waste management. The data obtained can be used to further undertake a life-cycle assessment study and/or to apply existing socio-economic methodologies to thoroughly assess impacts and benefits of food waste management.
This research was funded by Engineering and Physical Sciences Research Council (EPSRC) UK, grant number EP/K030957/1.
- Mechanical, Electrical and Manufacturing Engineering