Food processing technology research and development activities have historically been
driven by large-scale manufacture upscaling drivers to profit from economies of scale. Increasing
demand for high-quality food with pioneering texture profiles, consumer needs for personalised
products impacting product formulation (i.e., fat, sugar and micronutrient content), and constrained
availability of ingredients and resources are pressuring industrialists to utilise alternative technologies
to enable a more sustainable food supply. Distributed and localised food manufacturing (DLM)
has been identified as a promising strategy towards future sustainable systems with technology
representing one of its cornerstones. Innovative methods and tools to support the selection of
the best alternative technologies for DLM are required. This paper provides an overview of food
processing technologies and includes a novel classification created to support future assessments.
A novel qualitative assessment method encompassing multiple criteria to understand specific food
technologies suitability for future DLM systems is presented. Finally, research benefits are explored
through the application of the assessment method to several selected technologies with promising
potential in future food manufacturing. The results demonstrate that this methodological approach
can assist in the adoption of DLM food systems through the selection of the best technologies
integrating individual manufacturer requirements.
Funding
This work was supported by the Engineering and Physical Sciences Research Council [grant number
EP/K030957/1], the EPSRC Centre for Innovative Manufacturing in Food.
History
School
Mechanical, Electrical and Manufacturing Engineering
Published in
Sustainability
Volume
11
Issue
12
Citation
GIMENEZ ESCALANTE, P. and RAHIMIFARD, S., 2019. A methodology to assess the suitability of food processing technologies for distributed localised manufacturing. Sustainability, 11(12): 3383.
This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/
Acceptance date
2019-06-14
Publication date
2019-06-19
Copyright date
2019
Notes
This is an Open Access Article. It is published by MDPI under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/