Projects overview
ETEKINA | HEAT PIPE TECHNOLOGY FOR THERMAL ENERGY RECOVERY IN INDUSTRIAL APPLICATIONS
01-10-2017
-30-09-2021
MARKET4.0 | A Multi-Sided Business Platform for Plug and Produce Industrial Product Service Systems
01-11-2018
-30-04-2022
As a customer, easy access to equipment manufacturers repositories or to manufacturing services. As an equipment or service provider, easy access to the market.
IDS RA configuration and implementation not only on a peer to peer basis, but creating a data space.
CyberFactory#1 | Addressing opportunities and threats for the Factory of the Future (FoF)
17-12-2018
-30-06-2022
ConnectedFactories 2 | Global-leading smart manufacturing through digital platforms, cross-cutting factors and skilled workforce
01-12-2019
-30-11-2022
DigiPrime | Digital Platform for Circular Economy in Cross-sectorial Sustainable Value Networks
01-01-2020
-31-12-2023
The Battery Pilot will aim at demonstrating that the DigiPrime platform can unlock a sustainable business case targeting the remanufacturing and re-use of second life Li-Ion battery cells with a cross-sectorial approach linking the e-mobility sector and the renewable energy sector, specifically focusing on solar and wind energy applications.
As the proactive exploitation of the DigiPrime platform enables the car-monitored SOH tracing and availability, less testing is needed to assess the residual capacity of the battery. Moreover, by knowing the structure of the battery packs, a decision support system can be implemented to adjust the de-and remanufacturing strategy accordingly and select the most proper cells for re-assembly second-life modules, thus unlocking a systematic circular value chain for Li-ion battery cells re-use. Furthermore, excessively degraded cells which cannot be re-used can be sent to high-value recycling, based on the knowledge of their material compositions.
SHOP4CF | Smart Human Oriented Platform for Connected Factories
01-01-2020
-31-12-2023
DIMOFAC | Digital Intelligent MOdular FACtories
01-10-2019
-31-03-2024
Main challenges identified are:
- Training the existing workforce to use the new technologies
- Support the start-up stages to overcome initial reluctance due to lack of knowledge and too many aspects to integrate, so that industrials does not know how to start
- Reassure and support manufacturers to better embrace innovative Industry 4.0 technologies through test-before-invest approach
- Creating positive image about the manufacturing industry in the new generation so that they are open to join manufacturing domain
- Use of standardisation and healthy collaborations
Training the existing workforce to use the new technologies is identified as a main challenge
RECLAIM | RE-manufaCturing and Refurbishment LArge Industrial equipMent
01-10-2019
-30-09-2023
REMODEL | Robotic tEchnologies for the Manipulation of cOmplex DeformablE Linear objects
01-11-2019
-31-10-2023
MERGING | Manipulation Enhancement through Robotic Guidance and Intelligent Novel Grippers
01-11-2019
-31-10-2023
Arrowhead Tools | Arrowhead Tools for Engineering of Digitalisation Solutions
01-05-2019
-31-07-2022
MADEin4 | Metrology Advances for Digitized ECS industry 4.0
01-04-2019
-30-09-2022
RebootIoTFactory | Reboot IoT Factory
01-03-2018
-30-04-2021
CSA-Industy4.E | Coordination and Support Action for Industry4.E
01-10-2018
-30-09-2020
ZDMP | Zero Defect Manufacturing Platform
01-01-2019
-30-06-2023
EFPF (European Factory Platform) | European Connected Factory Platform for Agile Manufacturing
01-01-2019
-31-12-2022
QU4LITY | Digital Reality in Zero Defect Manufacturing
01-01-2019
-31-07-2022
The main innovation will be represented by the introduction in production of MPFQ model fused with AQ control loops: Functional Integration and Correlation between Material, Quality, Process and Appliance Functions.
One the one hand, some pilot owners expect that no particular skills will be requested after the QU4LITY project development implementations. For example:
- all systems should remain accessible by the majority of the workers without specific expertise or knowledge (where for instance each correlation system has to remain within a blackbox and only provide rules outputs for production lines).
- The AR app and the first training on the machine will be enough for start the production with new operators on the line.
- In essence the job profile will remain the same, however, the operators need to understand & be able to work with these new technologies. This requires some basic knowledge on the (digitalized) systems, for the operators a lot can be captured in SOP’s (standard operation procedures), but the technical support staff should also have some basic knowledge on the workings and the hardware/software side of the systems in order to be able to support the shopfloor where needed
New job profiles and associated skills are: Digital Business Processes Analyst, Expert in Machine Learning Algorithms, DevOps Development knowledge, Data scientist (programming and statistical knowledge), Artificial Inteligence knowledge, Cybersecurity expert, Ontology architects and modellers in MBSE, Digitalized systems Shopfloor worker, Digital and connectivity engineering, New systems integration Manufacturing Engineer, Cloud -Data Formats - Data analytics Engineer, Product, manufacturing and quality global knowledge.
Re- and upskilling needs were identified in the following areas: AI and Data analytics; Agile development, Multi disciplinary project management (IT, mechanical, electrical engineering); Design Thinking; Standardization; Data Analysis and Data Space technology for Manufacturing; IT Skills : Docker environment and languages like phyton of json; Data Analytics : basic skills , BI softwares
Programming languages such as C#, C ++, HTML, Java, Microsoft .NET and SQL Server ; data tools for data cleaning and preprocessing, data parsing, data feature engineering; machine to machine (M2M) data and protocols; Machine Learning Skilling for all languages/ ML Systems; Data analysis skills
The following knowledge delivery mechanism where identified as relevant: AR/VR, gamification, on-the-job training, vocational training, MooCs (Massive Open Online Courses)
- For newcomers to the field of Zero Defect Manufacturing, MOOCs are the way to go, since they can cover more aspects of the Industry4.0 and ZDM, not just the data science part. For the work force already in place, vocational training or on the job training would be recommended, herewith quickly adapting to the new working situations. On the job training would be enough to transmit knowledge of the technology. The solution develop has to be as user friendly as possible and be quickly understandable either on the HMI aspect and on the hardware side.
SHAREWORK | Safe and effective HumAn-Robot coopEration toWards a better cOmpetiveness on cuRrent automation lacK manufacturing processes.
01-11-2018
-31-10-2022
CoLLaboratE | Co-production CeLL performing Human-Robot Collaborative AssEmbly
01-10-2018
-31-03-2022
In order for CoLLaboratE to successfully realize its vision, several prerequisites were set in the form of major Scientific and Technological Objectives throughout the project duration. These are summarized in the following points:
Objective 1: To equip the robotic agents with basic collaboration skills easily adaptable to specific tasks
Objective 2: To develop a framework that enables non-experts teaching human-robot collaborative tasks from demonstration
Objective 3: The development of technologies that will enable autonomous assembly policy learning and policy improvement
Objective 4: To develop advanced safety strategies allowing effective human robot cooperation with no barriers and ergonomic performance monitoring
Objective 5: To develop techniques for controlling the production line while making optimal use of the resources by generating efficient production plans, employing reconfigurable hardware design, and utilising AGV’s with increased autonomy
Objective 6: To investigate the impact of Human-Robot Collaboration to the workers’ job satisfaction, as well as test easily applicable interventions in order to increase trust, satisfaction and performance
Objective 7: To validate CoLLaboratE system’s ability to facilitate genuine collaboration between robots and humans
The CoLLaboratE project will have profound impact on strengthening the competitiveness and growth of companies in the manufacturing sector:
- CoLLaboratE developed a co-production cell for manufacturing production lines, capable to perform assembly operations through human-robot collaboration. This cell is the result of inter-disciplinary technological advances that were realized during the project, in a series of highly significant areas related to robotics and artificial intelligence. The proposed system has been demonstrated and evaluated at TRL6, being ready for commercial take-up, allowing this assembled knowledge to be in turn, rapidly integrated in real production lines of industries and SMEs.
- CoLLaboratE developed technologies for autonomous and collaborative assembly learning and teaching methods by non-experts so that no explicit robot programming is required. As the products of industries, such as LCD TV’s rapidly evolve, flexibility so as to easily adapt in a new assembly task regarding a new product, is a major quality sought for modern assembly lines. Robots that need several months to be programmed and start working on the task are a rather unrealistic solution. Given the (a) time-consuming programming process typically required for industrial robots and (b) difficulties posed to robots from uncertainties in small parts assembly, cheap labour hands of low cost countries (LCCs) have so far been typically utilized instead of robotic solutions, through LCC assembly outsourcing strategies.
- CoLLaboratE service portfolio included a set of innovative fast and flexible manufacturing techniques, combining the benefits of the reconfigurable hardware design and modern ICT technologies (e.g. AΙ, learning toolkit, digitization of assembling processes)
- CoLLaboratE introduced novel AGVs on shop floors with enhanced capabilities, that apart from motion planning and obstacle detection, they are also capable of detecting the intentions of human users in the factory in order to provide flexibility and facilitate the production process, along with optimal use of resources.
- CoLLaboratE reduced delivery times and costs, whereas robot assembly techniques will also allow a much greater degree of customization and product variability. As it is highlighted in the euRobotics AISBL Strategic Research Agenda, the use of robotics in production is a key factor in making manufacturing within Europe economically viable; locating manufacturing in Europe through robotic solutions that will suppress LCC outsourcing is a major goal for the near future. Through flexible assembly lines, the manufacturing companies will be offered with great leverage over their innovation capacity and integration of new knowledge into their products.
- CoLLaboratE paved the way for a new era in industrial assembly lines, where robots will present genuine collaboration with the human workers and will allow manufacturing industries to establish in-house robotic-based assembly lines, capable to rapidly adapt in continuously evolving products. Through its advances, SMEs holding robotic-based assembly lines, will benefit by acting as subcontractors for large industries, since they will be a viable alternative to LCC outsourcing.
It becomes clear that the CoLLaboratE project has profound potential to strengthen the competitiveness and growth of companies and bring back production to Europe, by implementing novel artificial intelligence technologies and integrating robots with collaborative skills in the production, meeting a specific, highly important need of European, as well as worldwide manufacturing industries toward their future growth and sustainability.
The target users for the CoLLaboratE system are manufacturing industries in need of flexible and affordable automation systems to boost their global competitiveness. Successful completion of CoLLaboratE will allow SMEs and large manufacturing companies in Europe to easily program assembly tasks and flexibly adapt to changes in the production pipeline. Such ease of use and rapid integration time of robotic assembly systems is expected to pave the way for step change in the adoption of not only collaborative robots, but a complete collaborative environment provided by the CoLLaboratE solution.
HR-Recycler | Hybrid Human-Robot RECYcling plant for electriCal and eLEctRonic equipment
01-12-2018
-30-11-2022
FIT4FoF | Making our Workforce Fit for the Factory of the Future
01-10-2018
-30-09-2021
Simplified and Efficient Selection of Suitable Manufacturing Equipment: For the equipment manufacturer, IDSRAM permits the trusted connection of the equipment repository with external apps (ESS), permitting (in a time-saving process) the best selection of a manufacturing equipment, thanks to accessible data that where not accessible before.
The MARKET4.0 Metal Domain Data Space propose two solutions: