Projects overview
KITT4SME | platform-enabled KITs of arTificial intelligence FOR an easy uptake by SMEs
01-10-2020
-31-03-2024
Better Factory | Grow your manufacturing business
01-10-2020
-30-09-2024
GRECO | Fostering a Next Generation of European Photovoltaic Society through Open Science
01-06-2018
-31-05-2021
ETEKINA | HEAT PIPE TECHNOLOGY FOR THERMAL ENERGY RECOVERY IN INDUSTRIAL APPLICATIONS
01-10-2017
-31-03-2022
R-ACES | fRamework for Actual Cooperation on Energy on Sites and Parks
01-06-2020
-31-03-2023
AI REGIO | Regions and DIHs alliance for AI-driven digital transformation of European Manufacturing SMEs
01-10-2020
-30-09-2023
STAR | Safe and Trusted Human Centric Artificial Intelligence in Future Manufacturing Lines
01-01-2021
-31-12-2023
COALA | COgnitive Assisted agile manufacturing for a LAbor force supported by trustworthy Artificial Intelligence
01-10-2020
-30-09-2023
COALA is a solution for cognitive assistance that consists of a composition of trustworthy AI components with a voice-enabled digital intelligent assistant as an interface.
COALA will contribute in the ongoing discussion about AI ethics and potential standards, monitor the standardization potential for worker education under consideration of AI competencies, and will use and contribute to IT standards. We will take into account available IT-related standards and use them when applicable. This includes normative standards as set by ISO and its national bodies, which are of high importance to industrial companies. We will assess standards proposed by major influential de-facto standardization bodies like W3C, OASIS, and OMG. Standardization topics concern:
- The technical system architecture level. Standardize communication protocols, data exchange formats, data exchange interfaces.
- The content level. Ontologies for the semantic data integration and the WHY engine.
- The process level. This includes innovation management system, terminology, terms and definitions, and tools and methods.
COALA calls for a new experience in human-machine collaboration: it fosters a vision of human-AI symbiosis in which AI augments its users instead of replacing and devaluing them. COALA aims to assist human reasoning, keep humans in decision making without directing them algorithmically.
COALA will develop a Digital Intelligent Assistant (DIA) that can advise blue collar workers, such as machine operators and line managers, in complex, agile, and quality-focused discrete or process manufacturing industry. At this concern, human-centred interaction with the assistant needs to consider aspects such as the instant availability of information, support to problem solving of an adaptive system (e.g. context-awareness, internal information parsing, and impact evaluation).
XMANAI | Explainable Manufacturing Artificial Intelligence
01-11-2020
-30-04-2024
ASSISTANT | leArning and robuSt deciSIon SupporT systems for agile mANufacTuring environments
01-11-2020
-31-10-2023
TEAMING.AI | Human-AI Teaming Platform for Maintaining and Evolving AI Systems in Manufacturing
01-01-2021
-30-06-2024
i4Q | Industrial Data Services for Quality Control in Smart Manufacturing
01-01-2021
-31-12-2023
I4MS4Ts | I4MS Tools and Technologies for Transformation
01-06-2020
-30-11-2022
TINKER | FABRICATION OF SENSOR PACKAGES ENABLED BY ADDITIVE MANUFACTURING
01-10-2020
-31-03-2024
InterQ | Interlinked Process, Product and Data Quality framework for Zero-Defects Manufacturing
01-11-2020
-31-10-2023
DAT4.ZERO | Data Reliability and Digitally-enhanced Quality Management for Zero Defect Manufacturing in Smart Factories and Ecosystems
01-10-2020
-31-03-2024
OPTIMAI | Optimizing Manufacturing Processes through Artificial Intelligence and Virtualization
01-01-2021
-30-06-2024
Grade2XL | Application of Functionally Graded Materials to Extra-Large Structures
01-03-2020
-31-08-2024
RFID Positioning System – Use of multiple RFID receivers within the cell would allow for 3D location tracking of the parts to be assembled in the system, ensuring parts are correctly present and in the right locations before proceeding.
User interfaces were designed in WinCC
Nikon K-CMM Metrology - By positioning LEDs on the robot end effector, and on the target parts, the K-CMM system can measure relative positioning to a very high degree of accuracy even over large distances.
Siemens TIA Portal, WinCC, PLCs – The lower level control of resources in the system was performed with Siemens brand programmable logic controllers
Nikon Adaptive Robotic Control (ARC) – this technology allows data from metrology systems to correct a robot controller’s coordinate system and compensate for inaccuracies and variability.
KUKA Robotics – Compatible with the ARC system, the KUKA robots were used for part positioning.
Siemens Totally Integrated Automation Portal (TIA Portal)
RFID Positioning System – Use of multiple RFID receivers within the cell would allow for 3D location tracking of the parts to be assembled in the system, ensuring parts are correctly present and in the right locations before proceeding.
User interfaces were designed in WinCC
Nikon K-CMM Metrology - By positioning LEDs on the robot end effector, and on the target parts, the K-CMM system can measure relative positioning to a very high degree of accuracy even over large distances.
Siemens TIA Portal, WinCC, PLCs – The lower level control of resources in the system was performed with Siemens brand programmable logic controllers
Nikon Adaptive Robotic Control (ARC) – this technology allows data from metrology systems to correct a robot controller’s coordinate system and compensate for inaccuracies and variability.
KUKA Robotics – Compatible with the ARC system, the KUKA robots were used for part positioning.
Siemens Totally Integrated Automation Portal (TIA Portal)
Grafana – Used for the creation of bespoke data visualisation solutions.
Python / Tensorflow / Pytorch – Used for the creation of bespoke machine learning algorithms and analysis processes.
Siemens Teamcenter, Process Simulate, PLCSIM Advanced, NX – The virtual commissioning system is based on Siemens’ suite of software solutions. This selection was based on the capabilities of the software itself, and on the use of Siemens hardware for the control of the demonstrator.