IMA Group joins seven new projects under the Next Generation EU programme

Published: 31-May-2024

The projects will focus on key Pharma 5.0 aspects, such as sustainability, artificial intelligence (AI) and robotics

IMA, a global specialist in the design and manufacture of machinery for pharma packaging and labelling, is directly participating in seven projects funded through the EU’s National Recovery and Resilience Plan. These projects — three of which are co-funded through BI-REX — aim to promote sustainability, digitalisation and the automation of industrial processes in collaboration with other partners. 

BI-REX is one of the eight national Competence Centres established by the Ministry of Economic Development and Made in Italy (formerly MISE) as part of its the Industry 4.0 plan. 

It represents a consortium that includes over 61 universities, research centres and companies focused on digital transformation and technological innovation.

The National Recovery and Resilience Plan falls within the context of the Next Generation EU programme and the EU’s Horizon Europe Framework programme for research and innovation.

The seven projects IMA is involved in are outlined below, grouped by aim:


Promoting sustainability 

  • QUEST: Quantification and reduction of the environmental impact of automated packaging processes through LCA and Ecodesign

The project focuses on creating an integrated approach to optimise practices involved in the management of automatic machines for packaging and wrapping, with particular attention to environmental sustainability. The activities concern the entire lifecycle of the machines, from conception to disposal, integrating existing laws and regulations.

  • BIO-LUSH: Biomass valorisation for sustainable and high-quality fibre materials

Within the project, processes for the optimal refining of biomass and nanometric fibrillation will be established to convert the sustainable fibres obtained into functional bio-based materials. The project will demonstrate the processing of biomass and the production (both at TRL5) of bio-based products such as edible packaging, antibacterial textiles and bio(nano)composite filaments printable in 3D for impact-resistant interior automotive products.

Doing more with AI

  • PLaaS+: IT and OT to transform traditional automation

The PLaaS+ (PLc as a Service) project aims to optimise the industrial automation sector through a virtualisation solution dedicated to industrial control systems. The goal is to integrate information technologies (IT) and automation technologies (OT) to develop smarter, more flexible and robust production systems.

  • AI4Work: Human-centric Digital Twin Approaches to Trustworthy AI and Robotics for Improved Working Conditions

The AI4Work project will investigate practical methods and tools for optimal job sharing between humans and artificial intelligence/robots. The vision of the AI4Work project is to enhance communication and collaboration between humans, artificial intelligence and robots, enabling improved working conditions.

Automation and robotics to enhance manufacturing efficiency

  • MATRIX: Robotic manipulation and transport of liquids for high-performance industrial applications

MATRIX will focus on the development and testing of techniques for handling liquid containers using high-dynamic robots. The proposed technology seeks to control the movement of robots to effectively manage liquid content, thus enhancing business competitiveness.

  • FLASH: Flexible laser-based manufacturing through precision photon distribution

The project will endeavour to enhance the technology of laser-based manufacturing, making it more flexible and reducing waste produced. FLASH will develop a flexible platform equipped with three integrated laser sources, allowing multi-wavelength emission. 

  • BIOTOOL-CHF: BIOmarker-based diagnostic TOOLkit to personalise pharmacological approaches in congestive heart failure

The BIOTOOL-CHF project is looking to develop a medical device to improve the effectiveness of diuretic therapy for patients with heart failure, integrating diagnostic and prognostic attributes with clinical and demographic patient characteristics to optimise personalised treatment regimes.

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