By Mark Naylor - 23 May 2016

Have you ever considered using mathematical modelling to simulate your own process?

As more companies in the food and drink industry are turning to mathematical modelling to develop and optimise their processes, knowing the advantages and pitfalls of this technology is becoming increasingly important.

A model is used to describe how a system works. This system could represent anything from the entire universe down to a single plant cell, but for today it represents a cake in the oven.

When modelling such a system, initial conditions such as the size and shape of the cake can be input numerically, and underlying factors such as the air flow inside the oven can be included by adding equations and additional parameters. Broadly speaking, there are two main uses of modelling:

1. To develop and improve scientific understanding of the system from previous observations and known relationships - e.g. learning more about the thermodynamic properties of the cake by studying the relationship between environment and product temperatures, or by modelling bubble formation during the bake.

2. To test the effect of change to a system - e.g. being able to predict the internal temperature of the cake when baking in an alternative oven design, or predicting baking times when the size of the cake is changed.

Bearing in mind that numerical models have limitations, their judicious use has the following advantages for food production and process development environments:

• Can provide improved efficiency in the food sector by offering a better understanding of the processes that are otherwise difficult to understand and lead to their over- or under-estimation.
• Has the potential to model new equipment/process/packaging/product designs before any purchases or engineering work is required.
• Can help predict design and scale-up issues - optimising loading patterns inside the cooker, ensuring that equipment is capable of providing sufficient processing, predicting potential blockages inside pipelines.
• Allows feasibility studies of new concepts and designs which are too complex, expensive or dangerous to build.
• Can be used when it is impractical or impossible to make practical measurements.
• Can help to reduce the number of practical experiments required - less interference with production plus any additional savings in reduction of energy, raw materials and waste products.
• Can be extrapolated to unexplored or unexplorable regions.
• Can test "What if" scenarios: for example, when baking a cake, one can easily check if the product quality (output) improves by varying the processing temperatures and times (input variables).

For further information on modelling, or to see how modelling could help with your issues, please get in touch to see how we can assist.