The problem of matching production and demand of fresh fruit produce is actual, and often people do not realise the implication of this issue on supply chain performance regarding profit, food waste, and shelf life. The objective of the activity was to teach the power of matching orders and demand with production. Both production and demand have random pattern studied and validated with data from the packing industry. Production is influenced by weather and by cultivation practices (e.g. irrigation, trimming, time of harvesting). Also, fruit size varies a lot. Ordering and demand had their pattern that could be varying by channels and influenced profoundly by promotion. The authors implement a discrete event model that allows the student to perform some order and demand adaptation to match the production. Actions to modify the demand imply promotion (that double sales but cut the profit per box by 50%), finding channels for different sizes of the fruits. The model also considers lead times (2 to 6 days) for product packing and transportation and show the effect of the student’s choices on supply chain performance in terms of supply chain profit, food waste, and shelf life. The model work step by step over a period of 40 days, allowing day by day decision from the user and plotting demand, storage and production day by day, in the deterministic and stochastic way. Through the use of the model, the user experiences the difficulties encountered in an industrial environment while trying to match production and demand of fresh, perishable products. The model interface and first students trials are presented in the paper.
SIMULATION GAME TO MATCH PRODUCTION AND DEMAND OF FRESH FRUIT MARKET
Sopegno, Alessandro;ROTA, PAOLO;Busato, Patrizia;Berruto, Remigio
2018-01-01
Abstract
The problem of matching production and demand of fresh fruit produce is actual, and often people do not realise the implication of this issue on supply chain performance regarding profit, food waste, and shelf life. The objective of the activity was to teach the power of matching orders and demand with production. Both production and demand have random pattern studied and validated with data from the packing industry. Production is influenced by weather and by cultivation practices (e.g. irrigation, trimming, time of harvesting). Also, fruit size varies a lot. Ordering and demand had their pattern that could be varying by channels and influenced profoundly by promotion. The authors implement a discrete event model that allows the student to perform some order and demand adaptation to match the production. Actions to modify the demand imply promotion (that double sales but cut the profit per box by 50%), finding channels for different sizes of the fruits. The model also considers lead times (2 to 6 days) for product packing and transportation and show the effect of the student’s choices on supply chain performance in terms of supply chain profit, food waste, and shelf life. The model work step by step over a period of 40 days, allowing day by day decision from the user and plotting demand, storage and production day by day, in the deterministic and stochastic way. Through the use of the model, the user experiences the difficulties encountered in an industrial environment while trying to match production and demand of fresh, perishable products. The model interface and first students trials are presented in the paper.File | Dimensione | Formato | |
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