Production scheduling in the food industry

In this paper we study the optimality of production schedules in the food industry. Specifically we are interested whether stochastic economic lot scheduling based on aggregated forecasts outperforms other lot sizing approaches. Empirical data on the operation’s customer side such as product variety, demand and inventory is used. Hybrid demand profiles are split into make-to-order (MTO) and make-to-stock (MTS) time series. We find that the MTS demand aggregation stabilizes, minimizes change-overs, and optimizes manufacturing