Fraunhofer Institute for Production Technology IPTResearch project "AGILEHAND"
Motivation: Optimized handling of deformable food products
The market for conveying systems, and in particular the robot segment for automated material handling, is an important market for EU manufacturers, accounting for 23% of the total market alone.
The robots developed by the companies enable the transport and further processing of various products. In particular, the handling, sorting and packaging of soft and deformable products such as raspberries, peaches or fish present special challenges for robots. The resulting challenges are to be met by the AGILEHAND project, which is funded by the European Union (EU).
Development of a holistic solution for effective and efficient sorting, handling and packaging of deformable products.
The aim of the project is to develop a solution to increase transparency along the product value chain, increase productivity for companies and reduce food waste. For this purpose, technologies for sorting, handling and agile, flexible reconfigurability of production lines are developed and elaborated as a solution in the form of different suites. These suites focus on the connection and management of intelligent sensor technology (Smart Sensing Suite), the development of robots for self-adaptive handling, sorting and packaging of products (Self-Adaptive Handling, Sorting and Packaging Suite) and the planning and control of agile, flexible and rapidly reconfigurable production lines (Agile, Flexible and Rapid Reconfigurable Suite). The elaborated results are implemented and validated using four different use cases from the food industry.
Our solution
On the Fraunhofer side, the focus is on elaborating two core areas of the Agile, Flexible and Rapidly Reconfigurable Suite. The first core area includes the design and development of a pro-duct-oriented traceability solution to comply with health regulations, capture relevant data across all steps of the process chain and improve the agility of the system. For this, marking and identification solutions will be screened, evaluated and implemented in the final suite.
In the other core area, solutions for optimizing the production configuration and planning of production systems are developed. Various algorithms for optimizing the production layout and machine settings will be developed and evaluated. The elaborated solutions will be implemented and validated within the four different pilot lines.
An innovation here is the traceability of deformable products from the food industry in combination with flexible machine selection and configuration along individual production and logistics steps.
Consortium
Project coordinator: Università Politecnica delle Marche, Ancona, Italy
Project partners
- Knowledgebiz Consulting - Sociedade de Consultoria Em Gestao Lda, Almada, Portugal
- Fondazione Bruno Kessler, Trento, Italiy
- Universitat Politècnica de València, Valencia, Spain
- Tampereen Korkeakoulusaatio SR, Tampere, Finnland
- Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e. V., Munich, Germany
- B2A S.r.l., Rovereto, Italy
- UNINOVA-Instituto de Desenvolvimento de Novas Tecnologias-Associacao, Caparica, Portugal
- Flanders’ Food, Brussels, Belgium
- Factor Social – Consultoria Em Psico-Sociologia e Ambiente Lda, Lisbon, Portugal
- Fundingbox Research Aps, Odense, Denmark
- Laboratoire Virtuel Européen dans le Domaine de l’Interopérabilité des Entreprises, Brussels, Belgium
- MARELEC Food Technologies, Nieuwpoort, Belgium
- Sant Orsola Società Cooperativa Agricola, Pergine Valsugana, Italy
- Multiscan Technologies S.L, Alicante, Spain
- AINIA, Paterna Valencia, Spain
- Produmar – Produtos Do Mar, S.a., Vila Do Conde, Portugal
- UNINFO Associazione, Turin, Italy
- Associacao Portuguesa para a Qualidade, Lissabon, Portugal
Funding body
The project is funded by the European Commission's Horizon Europe research and innovation program (Research and Innovation Action). The project is part of the European Health and Digital Executive Agency (HaDEA) of the European Commission.
Funding reference: 101092043