Maschines for optimal portioning of food products were modeled and simulated. Thus, new machine parameters can changed without costly tests, and new control algorithm can be tuned in silico.

Case study: Modelling and Simulation of a food slicing machine

Slicing irregularly shaped products into portions of prescribed weight is difficult.

An important task for food industry is to slice products into portions of optimal weight, that is, respecting the legal restriction on the minimal weight of the portions on the one hand, and having as little overweight as possible on the other hand. If the products are irregularly shaped, such as cheese with holes or bacon, this is difficult to achieve.

My customer is a leader in the market for food slicing machines. Their machines use sensors like balances and image processing to control the weight and automatically adapt the slicing process. Changes to machine parameters and configuration can entail costly tests. Also, adapting the machine parameters to new products can be difficult for users.

For this reason, I developed for this customer a mathematical model and a configurable simulation of their machine, including different types of sensors and the control algorithms. The simulation was successfully validated by the customer. Using this simulation software, it is now possible to predict the effect of changing machine parameters at minimal costs, to easily optimise control parameters and to evaluate new approaches to optimal control of the machine.