A central task in the iProcess project is to understand variations based on use of Big Data from novel rapid and on-line measuring methods for raw materials and product differentiation. TINE has expressed need for measuring different quality parameters of milk used for cheese productions, different parameters in cheese making processes and quality parameters in both fresh and ripen cheese in order to use Big Data strategy to identify the connections between milk qualities, processing parameters and the quality of the final cheese product. The final goal is to handle and control relevant parameters to obtain standard end-product quality.
Robotic cutting operation of pork leg (ham) is another research activity in the iProcess project. From a research perspective, this case is an interesting research activity involving several different tasks from 3D visual recognition, 3D CAD modelling based on internal characterisation, visual servoing, machine learning, robot control and gripper tool design. The initial approach and aim for the researchers working with this is to be able to reproduce robotically the cuts made from a skilled operator. As time and the work progresses more complexity will be added to the approach.