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Simulation and Optimization in the Beverage Industry


A beverage company, which was planning to increase its production, had some concerns about the different capacities presenting its production process to meet an increase in demand. 


The company is currently operating at high production levels, resulting from constant growth over time. A continuation of this growth is expected and, as such, a simulation analysis of the process has been carried out.

The company receives different types of raw materials that are stored to meet production needs. These different raw materials give rise to a product with several possible derivations. In addition to final products, the production process also returns waste that is recovered and sold or used. 


The storage costs of raw materials and the final product are high and are therefore one of the main optimization goals of the simulation.



In order to analyse the process and given the difficulty in obtaining existing data in the company, it was necessary to question the team on the various information required, as well as on an observation of the process in the field. 

The results were based on the one-year period, and several simulations were carried out during the same year to obtain data with an error probability of less than 5%. The simulation incorporated data such as : 

  • Statistical requirements and distribution of raw materials used ; 
  • Statistical data on the quantity and volume of shipment of the final product ; 
  • Transport times of materials between processing points ; 
  • Operation costs and corresponding shifts, availability and the probability of their unavailability ; 
  • Equipment efficiency and maintenance time. 


A production exchange of 10% between the final product 1 and the final product 2 gives rise to an operating profit of more than EUR 48000. 


The simulation not only provided a large amount of dynamic data to the managers of the industrial process for decision making, but also supported the company’s growth decisions from a financial and resource perspective. In the presence of different types of final products, as is the case, it is possible to define priority levels in real time, according to the expected results obtained by the simulation. 


Acknowledgements : Salma El Akraa e Kenza Chajia

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