MODUL4R joined the ONE4ALL, MARS and MODAPTO research projects to forge the AMiMO Cluster.
AMiMO stands for Automated Manufacturing with Intelligent Modules and is a strategic cluster of EU funded projects, all sharing an aligned research focus on “Excellence in distributed control and modular manufacturing”.
Funded by the Horizon Europe Programme, these projects primarily aim to explore the modularity of production systems that will enable flexible production, through cyber-physical modules.
Objectives
Expand the projects’ impact beyond individual schemes.
Contribute significantly to the dissemination and communication of cutting-edge scientific developments.
Facilitate resource exchange among experts who share an aligned research mission.
Strengthen the ties and cooperation among EU-funded research initiatives.
The 3 projects that teamed up with MODUL4R and created the AMiMO cluster
ONE4ALL Agile and modular cyber-physical technologies supported by data-driven digital tools to reinforce manufacturing resilience
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ONE4ALL aims to develop self-reconfigurable mobile collaborative robots embedded with IIOT devices for real-time monitorisation and interconnectivity; this technology will allow to digitally replicate the productive processes through data-driven digital twins and manage it by a self-learning AI-based distributed and multidisciplinary decision support system.
The higher objective will be to boost manufacturing plants’ transformation, with a focus on SMEs, towards industry 5.0, reinforcing their resilience under unexpected changes.
The potential of ONE4ALL will be demonstrated in two relevant environments from different sectors: agri-food and pharmaceutical. Moreover, an adaptive training programme for digital upskilling will be implemented over the entire project to prepare the workforce for the I5.0 transformation and fully exploit the potential of the technologies
MARS Manufacturing Architecture for Resilience and Sustainability
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The European project MARS aims to revolutionise the manufacturing industry by introducing extreme flexibility without compromising product requirements, quality, or sustainability. MARS aims to achieve this by leveraging advanced technologies such as Artificial intelligence (AI), Internet of Things (IoT), and cloud and edge computing to create a highly adaptable and dynamic manufacturing environment.
Through these technologies MARS creates an interconnected and intelligent manufacturing ecosystem that seamlessly integrates with the supply chain and enables real-time monitoring and control. MARS will hence enable manufacturers to respond to changes in demand and supply quickly and efficiently.
MODAPTO Modular Manufacturing and Distributed Control via Interoperable Digital Twins
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MODAPTO envisions a future where industrial systems are highly adaptable, comprised of modules, and empowered by distributed intelligence through interoperable Digital Twins (DTs). MODAPTO brings the advantages of a global perspective to production by facilitating collective intelligence within modular production setups. This fosters effective design, reconfiguration, and decision support for modules and production lines. MODAPTO's primary goal is to provide a versatile framework for modular manufacturing. This framework can be tailored to suit the specific requirements of any production module, process, or manufacturer. It supports activities such as high-level design, reconfiguration, and optimization decision-making. Additionally, it enables the use of distributed intelligence and control over modules through interoperable DTs.
MODAPTO draws inspiration from three distinct use cases, involving four different manufacturers. These manufacturers encounter varying challenges related to modular design and reconfiguration at different levels: machine, process step, and production process. These use cases serve as practical examples, showcasing the flexibility of the MODAPTO approach in addressing a wide array of modular manufacturing aspects. This adaptability leads to significant improvements in key performance indicators (KPIs), including efficiency, cost, quality, decision-making, energy efficiency, and environmental considerations.