1. Proceedings
  2. I3M
  3. 2018
  4. FOODOPS
  5. 10.46354/i3m.2018.foodops.003

Simulation in food catering industry. A dashboard of performance indicators

  • a Alessandro Tufano  ,
  • b Riccardo Accorsi   ,
  • c Andrea Gallo  ,
  • d Riccardo Manzini  
  • a, b, c,dDepartment of Industrial Engineering (DIN), Alma Mater Studiorum - University of Bologna, Viale del
    Risorgimento, 2, 40122 – Bologna – Italy
Cite as
Tufano A., Accorsi R., Gallo A., Manzini R. (2018). Simulation in food catering industry. A dashboard of performance indicators. Proceedings of the 4th International Food Operations and Processing Simulation Workshop (FoodOPS 2018), pp. 20-27. DOI: https://doi.org/10.46354/i3m.2018.foodops.003
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Abstract

Contract catering industry is concerned with the production of ready-to-eat meals for schools, hospitals and private companies. The structure of this market is highly competitive, and customers are rarely willing to pay a high price for this catering service. A single production sites may be demanded up to 10.000 meals per day and these operations can hardly be managed via rule of thumbs without any quantitative decision support tool. This situation is common at several stages of a food supply chain and the methodologies presented in this paper are addressed to any food batch production system with similar complexity and trade-offs. This paper proposes an original KPI dashboard, designed to control costs, time and quality efficiency and helping managers to identify criticalities. Special emphasis is given on food safety control which is the management’s main concern and must be carefully monitored in each stage of the production. To calculate the value of KPIs a Montecarlo simulation approach is used to deal with production complexity and uncertainty. A case study showcases the potential of simulation in this complex industrial field. The case study illustrates an application of the methodology on an Italian company suffering local recipe contamination. The company aims at defining the best standard for production, identifying cycles being sustainable from an economic and environmental point of view.

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