Analysis and Optimization of the Production Process of Cooked Sausage Meat Matrices

In the production of cooked sausages a critical step for product quality is the cutting process, where the comminuting and mixing of meat, fat, ice and spices are carried out. These processes take usually place in bowl cutters, which main control parameters are the working time, knife geometry (shape and sharpness) and rotational velocities of the knives and the bowl. The choice of the geometry and sharpness of the knives influences not only the meat matrix properties (mechanical, rheological, etc.) and, as a consequence, the sensory value of the sausages (size of connective tissue particles, water binding, etc.), but also the energetic demand for the production. However, the cutting process proves to be understood only fragmentarily due to the complex colloid chemical and mechanical behavior of the product. This is documented on the one hand by numerous knife types on the market, extremely empirical approach during determination of geometry and process parameters in practice as well as, on the other hand, by contradictory statements and explanation approaches of observed phenomena present in literature. The present contribution applies numerical simulations to analyze thermo fluid mechanical phenomena, e.g. shear stresses, during the cutting process of the non-Newtonian meat matrix. Combining these results with selected experimental investigations from literature, e.g. sensory properties, knife geometry, velocity of the knife and bowl, improvements of the cutting and mixing process are proposed using cognitive algorithms (Artificial neural networks) aiming at an optimization regarding energy and time demand and product quality.