Within the Food processing innovation package we're working on four projects:
Agrifood 14: Dark fruit factory
Overview of our project
Agrifood 14
Dark fruit factory
This project focuses on reducing manual labor in the sorting and packaging of fruit through further robotization and automation of the most labor-intensive processes. The optimization of existing technologies such as the Smartpackr and Automatic Traypacker for use in packing stations is central. Work is being done to expand the application areas for packaging robots to various types of fruit such as pears and citrus fruits, and to advanced automatic quality control systems that use multispectral recognition and machine learning. The development of logistic systems such as integration with high-bay warehouses and automated guided vehicles (AGVs), and the combination of these technologies into an efficient picking and sorting process are also key focuses.
Within Agrifood15, we are developing a flexible and modular meal production line controlled by advanced management software. This production line automatically adjusts based on the production order, where the process sequence, actuators, sensors, packaging, and ingredients are optimized for the efficient production of mainly Ready to eat and Ready to cook meals, as well as fresh meat products. The line utilizes techniques such as blockchain, advanced line control, and modular system architecture to meet high quality requirements and flexibility in production processes.
Agrifood 15
Ready to go (m)eat
Agrifood 16
Ready made meals
The project focuses on developing flexible and efficient automation and robotization for meal producers, particularly aimed at SMEs, to address the challenges of batch production, inflexible batch sizes, and a growing scarcity of labor. By using mobile cobots that can perform various tasks and be flexibly deployed at different workplaces, the aim is to improve production processes, increase labor efficiency, and reduce the likelihood of errors, while also meeting requirements for food safety and quality control.
Within this project, we develop and integrate sensor-driven technologies for central quality control and decentralized production in tea plantations. This includes managing all production steps, from post-harvest quality control to packaging, with a continuously monitored and self-learning system to ensure consistent quality for the retail market. The project also involves the development of a mobile, digitally controlled process and a new product: 'teabars', packaging-free tea in bar form, with each portion suitable for one cup of tea. The project explores whether the production of teabars is better centralized or localized, focusing on new sensors, AI, and digital twin technologies for optimized process control.