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The digitisation of food manufacturing to reduce waste – Case study of a ready meal factory

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journal contribution
posted on 2019-04-02, 11:01 authored by Sandeep Jagtap, Shahin RahimifardShahin Rahimifard
Generation of food waste (FW) continues to be a global challenge and high on the political agenda. One of the main reasons for its generation is the absence of detailed data on the amount, timing and reasons for created waste. This paper discusses the design, the application and investigates the Internet of Things (IoT) based FW monitoring system to capture waste data during manufacturing in real-time and make it available to all the stakeholders in a food supply chain (FSC). A case study of ready-meal factory comprises of design and architecture for tracking FW including both hardware and software, its implementation in the factory and the positive data-driven results achieved. The case study demonstrates the benefits of digital FW tracking system including the FW reduction of 60.7%, better real-time visibility of the FW hotspots, reasons for waste generations, reliable data, operational improvements and employee behavioural transformation. Although the system replaced the paper-based manual system of tracking FW in the factory, it still needed human input to confirm the waste and was prone to human errors. Overall, the implementation of an IoT-based FW tracking system resulted in a reduction of FW and created a positive environmental and financial impact.

Funding

This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) Centre for Innovative Manufacturing in Food [Reference: EP/K030957/1].

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Waste Management

Volume

87

Issue

2019

Pages

387 - 397

Citation

JAGTAP, S. and RAHIMIFARD, S., 2019. The digitisation of food manufacturing to reduce waste – Case study of a ready meal factory. Waste Management, 87, pp.387-397.

Publisher

Elsevier

Version

  • VoR (Version of Record)

Publisher statement

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

2019-02-06

Publication date

2019-02-16

Notes

This is an Open Access article. It is published by Elsevier under the Creative Commons Attribution 4.0 International Licence (CC BY). Full details of this licence are available at: https://creativecommons.org/licenses/by/4.0/

ISSN

0956-053X

Language

  • en

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