Quality-aware control for optimizing meat supply chains

J. P. Sprong, X. Lin*, J. M. Maestre, R. R. Negenborn

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)
111 Downloads (Pure)

Abstract

Controlling food quality and reducing waste is one of the most challenging tasks in the food industry, as it is facing high rates of wastage, leading to negative environmental impact. This research focuses on improving the scheduling and control of the supply chain of Irish lamb meat using real-time quality and temperature information. Temperature controlled reefers and sensor technologies can be used to monitor and set the temperature during transport and storage. In order to minimize waste, while at the same time optimizing cooling and transport costs, a mathematical model is proposed. The model consists of two aspects. The quality aspect considers the shelf life of Irish lamb which is related to temperature. The logistic aspect considers supply chain scheduling. With this model, a strategy is proposed to determine the movements of meat, as well as the temperature setting of cooling equipment. Results of simulation experiments indicate a sustainable approach can reduce or even eliminate waste and decrease operational costs when real-time monitoring and control is used.

Original languageEnglish
Title of host publicationProceedings of the 18th European Control Conference (ECC 2019)
Place of PublicationPiscataway, NJ, USA
PublisherIEEE
Pages3867-3872
ISBN (Electronic)978-3-907144-00-8
DOIs
Publication statusPublished - 2019
EventECC 2019: 18th European Control Conference - Napoli, Italy
Duration: 25 Jun 201928 Jun 2019

Conference

ConferenceECC 2019: 18th European Control Conference
Country/TerritoryItaly
CityNapoli
Period25/06/1928/06/19

Bibliographical note

Accepted Author Manuscript

Keywords

  • Cooling costs
  • Fresh food logistics
  • Meat supply chain
  • Mixed-integer linear programming
  • Quality-aware modeling
  • Shelf life

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