REIF | Resource-efficient, Economic and Intelligent Foodchain

In order to ensure a holistic view of food waste, the first of a total of eight sub-projects of the REIF research project will establish an AI ecosystem that integrates stakeholders from all stages of the value chain. In order to fully capture and describe the ecosystem in the food industry, organizational and economic as well as technical perspectives have to be considered. The core of the REIF ecosystem is the REIF platform, which represents the central instance within the ecosystem for the integration of all stakeholders.

The development, implementation and validation of specific AI solutions for the food industry will be carried out in further subprojects in the form of concrete use cases. Based on the established ecosystem, an optimized planning and control of value-adding processes from agriculture to the end consumer is to be designed with the help of artificial intelligence methods on both an inter- and intra-organizational level in order to reduce overall waste.

In order to reduce food waste, REIF follows a dual approach of minimizing overproduction and avoiding rejects. On the one hand, the improved data and information exchange along the value chain should not only minimize the bullwhip effect, but also use AI to forecast consumer demand more accurately. On the other hand, AI should enable production planning and control, as well as production facilities and production processes, to react quickly to fluctuating demand as well as to fluctuating raw material quality.

In the REIF project, the Fraunhofer IGCV is responsible, among other things, for the standardization of data structures and the development of standardized procedures to simplify and accelerate AI integration in systems and business processes. By developing and validating cross-company optimization approaches and business models for the REIF platform, we make a significant contribution to minimizing waste through improved communication and holistic optimization. Within the scope of the fields of application, we develop AI solutions such as AI-based plant control or dynamic adjustment of product prices depending on shelf life and forecast demand.