Projects overview
MANU-SQUARE | MANUfacturing ecoSystem of QUAlified Resources Exchange
01-01-2018
-30-06-2021
FACTORY-IN-A-DAY | Factory-in-a-day
01-10-2013
-30-09-2017
I-RAMPÂł | Intelligent Reconfigurable Machines for Smart Plug&Produce Production
01-10-2012
-30-09-2015
MULTI-FUN | MULTI-FUN
01-03-2020
-28-02-2023
EnerMan | ENERgy-efficient manufacturing system MANagement
01-01-2021
-30-04-2024
CAPRI | Cognitive Automation Platform for European PRocess Industry digital transformation
01-04-2020
-30-09-2023
Go-DIP | MANAGING DIGITAL INTELLECTUAL PROPERTY IN MANUFACTURING SMES DIGITALIZATION PROCESSES
01-04-2021
-30-04-2022
SESAME | Secure and Safe Multi-Robot Systems
01-01-2021
-31-12-2023
Waste2BioComp | Converting organic waste into sustainable bio-based components
01-06-2022
-31-05-2025
OPTIMAL | Automated Maskless Laser Lithography Platform for First Time Right Mixed Scale Patterning
01-10-2022
-30-09-2026
Fluently | Fluently - the essence of human-robot interaction
01-06-2022
-31-05-2025
AMBIANCE | Advanced Manufacturing of Bio-Based Products for Urban outdoor applications through Innovative characterization, digital technologies and circular approach
01-06-2022
-31-05-2026
A workshop organised by CRIT within the spec of AMBIANCE's dissemination efforts.
ENGINE | Zero-defect manufacturing for green transition in Europe
01-06-2022
-31-05-2025
ZDZW | Non-Destructive Inspection Services for Digitally Enhanced Zero Waste Manufacturing
01-09-2022
-31-08-2025
VITAL | InnoVatIve processing Technologies for bio-based foAmed thermopLastics
01-06-2022
-31-05-2025
TURBO | Towards tURbine Blade production with zero waste
01-10-2022
-31-03-2026
AI-PRISM | AI Powered human-centred Robot Interactions for Smart Manufacturing
01-10-2022
-30-09-2025
Circular TwAIn | AI Platform for Integrated Sustainable and Circular Manufacturing
01-07-2022
-30-06-2025
This pilot focuses on reducing the CO2 emissions and energy consumption that derive from the production of Ethylene Oxide and Ethylene Glycol
s-X-AIPI | self-X Artificial Intelligence for European Process Industry digital transformation
01-05-2022
-30-04-2025
The optimization of the use of resources during the selection of the aluminium recipes will be at the core of the IDSS with the aim of optimizing the overall process, reducing waste, and reducing polluting emissions.
To improve the efficiency of the whole value chain, AI apps will be used in predictive diagnosis of equipment efficiency to infer energy savings in production plant and maintenance optimization.
Self-X detection, self-X- diagnose and self-repair concepts will serve as a basis for the process control tool to be developed by the Steel Team.
OPENZDM | Open Platform for Realising Zero Defects in Cyber-Physical Manufacturing
01-06-2022
-30-11-2025
In the demonstrator of SONAE Arauco ES, the openZDM digital tools and platform will be used to achieve the following:- improvement of data collection and in-situ monitoring, namely in what concerns time-related annotation
- improvement of inspection of quality issues through artificial intelligence and digital-twin technology.
- further advances in predictive quality based on data-driven and model-driven approaches for defect prediction and quality assessment.
- improvement in manufacturing decision making for ZDM strategies and process adaptation. This will also include recommendation models for new products, an explainable AI approach for a better understanding of Machine Learning decisions and a graphical user interface through UX/UI strategies.
thus effectively support productivity through the following aspects:
1. Improved decision-making at the plant level to reduce defects towards a zero defects paradigm
2. Improved product development (faster and with less waste generated)
3. Improved evaluation of machinery components
The vision of the future process with the contribution of the openZDM solutions targets an improved decision-making at the plant level to reduce defects towards a zero defects paradigm, that will facilitate defect prediction and recommendation of production recipes to adjust machine parameters according to predicted defects. In turn, improved products can be developed using the data-driven knowledge acquired, resulting in less wasted material. Towards this direction, the openZDM project performed an LCA at the beginning ot he project to compare it with the final one and also it supports integration through its platform to an LCA tool for on-demand LCA.
OPENZDM solutions for AI quality assessment and decision support aim for data driven defect prediction and estimation of machine components degradation through drifts in data distribution. The main goal is to predict defects such as broken paper, dust or glued paper so that changes in machinery/parameters can be performed and the defect avoided and also to estimate degradation based on slight and smooth changes in the process start occurring due to component wear-out / degradation and, if data is representative enough, it may be different data distributions in time.
OPENZDM is expected to contribute to the SONAE Arauco use case in the aspects of proactive quality control towards zero-defect manufacturing through the digital twin enabled machine learning approaches for data analytics and quality assessment.
5G-TIMBER | Secure 5G-Enabled Twin Transition for Europe's TIMBER Industry Sector
01-06-2022
-31-05-2025