A Methodology for the Selection of Industrial Robots in Food Handling (Bader and Rahimifard, 2020) (1).pdf (1.84 MB)
0/0

A methodology for the selection of industrial robots in food handling

Download (1.84 MB)
journal contribution
posted on 02.06.2020 by Farah Bader, Shahin Rahimifard
As the global population continues to rise and consumer demand for a wider variety of food products increases, food manufacturers are exploring various strategies, methods and tools to change and adapt. Furthermore, restriction in access to low-cost labour and introduction of more stringent legislation are forcing the food industry to update their production processes. Industrial robots, a pillar of Industry 4.0, promises many benefits to the food manufacturing industry, especially in responding to these new challenges. The integration of such automation into food manufacturing has been a slow process in comparison to other manufacturing sectors and has largely been limited to packaging and palletising. This research aims to improve the application of industrial robots within food manufacturing through definition of a methodology for the identification of a flexible automation solution for a specific production requirement. The paper explores the four steps within the Food Industrial Robot Methodology (FIRM), through which users define, classify and identify their foodstuff and automation solution. The application of FIRM is exemplified through an industrial case study to support food manufacturers investigating the potential benefits of utilising industrial robots within their production systems.

Funding

EPSRC Centre for Innovative Manufacturing in Food

Engineering and Physical Sciences Research Council

Find out more...

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Innovative Food Science & Emerging Technologies

Volume

64

Pages

102379

Publisher

Elsevier BV

Version

VoR (Version of Record)

Rights holder

© The authors

Publisher statement

This is an Open Access Article. It is published by Elsevier 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/

Acceptance date

08/05/2020

Publication date

2020-05-18

Copyright date

2020

ISSN

1466-8564

Language

en

Depositor

Miss Farah Nabil K Bader . Deposit date: 2 June 2020

Article number

102379

Licence

Exports

Logo branding

Categories

Licence

Exports