The food industry in Norway prioritizes flexible robotic automation as means to be able to cope with the high biological variation in food raw material and to maximize the raw material utilization. Therefore, expectations towards such solutions are high since it is expected that flexible robotic automation will be able to increase profitability for the food industry in their production operations.
The research focus to develop flexible automation solutions for the food industry is to develop new and effective methods that will be able to substitute human based manual operations by developing solutions that integrate artificial eye (camera), brain (deep learning), and hand (robot arm).
SINTEF Ocean, in collaboration with leading national and international research institutes, is conducting research to develop new concepts for better prediction of raw material quality using Big Data and deep learning, enable robotic handling and processing of raw material, improve information flow along the food value chain, and develop new business models in order to maximize the innovation process from research to industrial applications. The focus in the beginning of the project was on defining relevant cases together with the industrial partners. The selected case studies are of high relevance to the industrial partners and are characterized by research activities of high level and novelty potential. These are complex challenges for which there are no commercial solutions, and we work multidisciplinary in order to maximize the effect of the research in iProcess.