Our involvement in current projects

On this page you will find a selection of current and completed projects we took part in in the last years.



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Predictive Q+ – PredictiveDataScience, TEC Eurolab, NV Bekaert SA, INNOVAPLAST

Advanced Software Platform for Streamlined Production Processes

Predictive Q+ is an advanced software platform for streamlined production processes. Originating from the automotive and steel wire industries, it serves as a comprehensive process control station, monitoring, detecting, and predicting operational and quality issues. Developed by the startup PredictiveDataScience in collaboration with industry partners and powered by AI, it offers tools for detailed analytics, disruption prediction, and optimization, enhancing quality and resource efficiency. Its versatile interface accommodates diverse data sources, catering to any manufacturing enterprise. Collaborating with partners within the consortium, Predictive Q+ expands its capabilities to other industries. TEC Eurolab leverages the platform for enhanced predictive maintenance of tomographs. NV Bekaert SA benefits from predictive maintenance for patenting and galvanizing lines and systems and quality control of wire products. INNOVAPLAST will use the platform for optimizing the process parameters in production of the ria-based bioplastic raw materials. Through collaborations, Predictive Q+ demonstrates its ability to drive innovation and address industry-specific challenges. Its versatile and powerful features, combined with a user-friendly interface, empower manufacturing enterprises to achieve agility, efficiency, and competitiveness. It enables companies to optimize their production processes, respond to market demands, and remain competitive in a dynamic economic environment.

kick-off meeting del progetto GIMCANA

Kick-off Meeting in Bratislava

kick-off meeting del progetto GIMCANA

Visiting TEC Eurolab’s Tomographic Center

HCP-bO – TEC Eurolab, Santer Reply, SUPSI, Industry Innovation Cluster, Smartzavod

Preference-based Optimization Algorithms for Industrial Processes

Many industrial processes are difficult to optimize due to the lack of performance index definition, unavailability of sensors (and, indeed, measurements), and difficulties in setting up objective functions. In such scenarios, expert operators’ knowledge drives the tune-up phase of the industrial processes/applications. Indeed, a programming-free approach to transfer such human knowledge to the production plant can be implemented to allow any operator to naturally/intuitively transfer his/her expertise to the target machine/robot.

kick-off meeting del progetto GIMCANA

The HCP-bO project exploits preference-based optimization algorithms to address such needs. By adopting such an approach, it is possible to train an algorithm by means of experiments performed by an expert operator, guiding the optimization process. The optimization algorithm can then elaborate a machine configuration depending on different objective functions. The system provides suggestions to the human operator, assisting him/her in the optimization activities. In addition, an enhanced version of this algorithm (including both qualitative and quantitative optimization capabilities) will be developed to maximize the flexibility of the optimization toolbox.

The developed algorithms (SUPSI + Santer Reply SpA) will be tested in two relevant use cases:

  • [Tec-Eurolab]: optimization of parameters of Industrial Computed Tomography scans;
  • [SMARTZAVOD]: optimization of polymer printing and automatic post-processing parameters for hybrid 3D printer.

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CAMPRES – TEC Eurolab, GHEPI, XBW Lithium Battery REvolution, ENEA, Fondazione Democenter-Sipe, CertiMaC Materials Energy Innovation

Innovative Composite Materials for the Containment of Battery Elements

The Kick-off Meeting of the CAMPRES Industrial Research Project was conducted as part of the “Call for strategic industrial research projects aimed at the priority areas of the Smart Specialization Strategy 2023-2024”, Action 1.1.2 “Support for collaborative research of research laboratories and universities with companies” of the Emilia-Romagna Region (PR-FESR EMILIA ROMAGNA 2021-2027).

CAMPRES focuses on the development of a family of innovative composite materials for the containment of battery elements for static and/or portable energy storage suitable for mass production with advanced injection molding technologies.

kick-off meeting del progetto GIMCANA

CAMPRES defines a modular architecture that offers flexibility in the design of Energy Storage, to meet the specific needs of different use scenarios and to encourage a more efficient and optimized installation. Mass production technology allows to reduce costs and improve the efficiency of the production process, ensuring rapid time-to-market. The proposed concept promotes the definition of standards that favor the interoperability of battery elements between different areas of use in line with the principles of the CIRCULAR ECONOMY and SECOND-LIFE management of Lithium Batteries

GIMCANA – TEC Eurolab, Future Technology Lab (UniPr), Centro Interdipartimentale di Ricerca Industriale Meccanica Avanzata e Materiali (UniBo), CRIT, BEAMIT, Blacks, Mind Composites, Bercella

High-Resistance Metal-Composite Joints

GIMCANA is a European Union co-funded project that will develop a new multi-material joining technology, to be applied to a wide range of structural components in any industrial sector, in order to promote the substitution of metal in favor of a fiber-reinforced polymer (PFR) and the resulting extreme weight reduction. The innovative technology, namely SLIM2CORE (Standalone Lattice Insert for Metal-COmposite COnnection REinforcement), is based on inserts made by low-cost, high-value Additive Manufacturing (AM), which will enable a stronger connection between metal and PFR. The project covers the entire value chain of the innovative technology, from materials, design, manufacturing, testing and quality control, evaluating its potential on a use case and the great impact of its adoption. GIMCANA will also be developed consistent with Circular Economy principles, showing how a high-performance metal-PFR component can be achieved by using recycled carbon fibers for the latter, and performing a life cycle analysis (LCA). The project has a duration of 30 months.

kick-off meeting del progetto GIMCANA

Our R&D Manager Fabio Esposito and TEC Eurolab’s Tomographic Center will contribute to the project for the testing and quality control part of the new technology, evaluating its overall performance through CT scans.

X-rAI – TEC Eurolab, Volkswagen, Fraunhofer, Loamics, Tvarit & Technische Universität Braunschweig

X-rAI – AI based X-ray analysis for quality prediction of casted products

X-rAI is a European co-funded project with a contribution of €1.148.723 by EIT Manufacturing. TEC Eurolab, together with other participants Volkswagen AG, Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V., Loamics, Technische Universität Braunschweig and Tvarit GmbH, will be working on the optimization of the casting process by using X-ray inspection to determine product quality. 

The foundry industry is one of the most energy-intensive industries in Germany. Therefore, the optimization of the processes with a resulting reduction of production defects is essential for a sustainable development of the industry. One way to optimize the casting processes is the use of digital tools to identify the non-linear and multicriterial dependencies in the processes, which significantly complicate the optimization. To derive these non-linear and multicriterial dependencies data analysis tools to analyze the data from the production process and the data from quality inspections are necessary. 

One quality inspection in the casting process is the X-ray inspection, which is mandatory for safety-relevant products. The inspection data and the X-ray image include various parameters to determine the product quality. Therefore, the data can be used to analyze dependencies between the product quality and the production processes.

AMULET Project – TEC Eurolab & ParaStruct

3DMgO – 3D Printing materials based on magnesium oxide binder

AMULET is a HORIZON 2020 project that aims to harness the innovation potential of SMEs in the field of light construction by creating new value chains through cross-sectoral knowledge exchange in the automotive, aerospace, aviation, energy and construction sectors. During 2022, TEC Eurolab presented, in collaboration with the Austrian company ParaStruct, the project “3DMgO – 3D Printing materials based on magnesium oxide binder.” The project assumes that many raw mineral materials are becoming rare due to over-exploitation of resources. In the 3DMgO project, ParaStruct and TEC Eurolab want to show how magnesium oxide residues produced during the magnesite calcination process and/or obtained from refractory ceramics residues from the steel industry can be made usable through additive manufacturing. The project aims to contribute to the circular economy and waste valorization in the construction world.

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