A key initiative of Europe is to accelerate the deployment of Data Spaces in different domains. Manufacturing Data Spaces are among the top 9 priorities set by the EC. Data sharing among manufacturing companies and with (service) providers will be increasing in the near future, demonstrating how sharing industrial data improves company operations. Both the discrete manufacturing and process industry are impacted by such a transformation. Consequently, the priority for manufacturing stakeholders will be to develop collaborative services based on a trusted and common framework for sharing and exchanging data and models multilaterally to overcome the interoperability challenge and implement next generation autonomous cross-enterprise industrial operations. Currently approaches to Digital Manufacturing Platforms (DMP) and Industrial Data Platforms (IDP) do lack the ability to consistently share data across organisations at scale. In fact, it is already acknowledged that peer-to-peer data sharing, especially when involving SMEs, will not scale to unveil high-quality data sharing for manufacturing value set above. The FIWARE Smart Industry Mission Support Committee (SIMSC) is playing a major role in this twin and green transition, facilitating the definition and adoption of common protocol and data models, as well as the spreading of enabling technologies such as Digital Twins and Artificial Intelligence. The session will drive you through the context analysis, the needs and benefits, the technologies adoption in relevant use cases and the offering of Testing and Experimental Facilities in several industrial domains.

1. Vienna, Austria
12-13 June, 2023
#FIWARESummit
From Data
to Value
OPEN SOURCE
OPEN STANDARDS
OPEN COMMUNITY
FIWARE for Sustainable Value Networks in
Manufacturing: connecting Data Sharing and
Interoperability, Digital Twin and AI platforms
Moderators:
Ernoe Kovacs (NEC), Angelo Marguglio (ENGINEERING)

2. Vienna, 12-13 June, 2023 | #FIWARESummit www.fiware.org
Sustainable Value Networks in Manufacturing :: Definitions
Sustainable Manufacturing can be defined as manufacturing processes intended to
• minimize negative environmental impacts,
• conserve energy and natural resources,
• be safe for employees, communities, and consumers
• be economically sounds
(Adapted from U.S. Department of Commerce)
Living with Complexities and Uncertainties

3. Vienna, 12-13 June, 2023 | #FIWARESummit www.fiware.org
Sustainable Value Networks in Manufacturing :: Motivations
Impact on the Environment
Pressure from
Society/Consumers/Customers
and other competitors
Interest in Efficiency
and Continuous Improvement
Scarcity of Resources
Pressure from Government
(Regulations, Penalties, and
Tax benefits)
Desire to maintain market
leadership

4. Vienna, 12-13 June, 2023 | #FIWARESummit www.fiware.org
Sustainable Value Networks in Manufacturing :: Barriers
Challenges
and
Barriers*
Lack of
Application
Experience
Lack of
Environmental
Laws
Lack of
Government
Support
Lack of Top
Level
Management
Cultural
Barriers
Knowledge
Gap
Finance/High
Costs
Difficult in
Operating and
Maintaining
Although green manufacturing is
driven by a number of positive
factors, the manufacturing and
process industries still face some
barriers and challenges that
hinder the application of green
manufacturing strategies in
practice.
* in Green Manufacturing

5. Data Spaces are where
sovereign data exchange
happens
• Join the duality: Consumers vs. Providers

6. Vienna, 12-13 June, 2023 | #FIWARESummit www.fiware.org
Sustainable Value Networks in Manufacturing :: EU Projects
Circular TwAIn with a holistic, domain agnostic approach aims at enhancing
the sustainability and the circularity of product and process industries with
tailored and easy to scale technological solutions.
CIRC-UITS digital solutions for the design, manufacture and management of
electronic components and end-of-life products through sustainable
methods, based on a circular models.
AIDEAS AI technologies for supporting the entire life cycle of industrial
equipment as a strategic instrument to improve sustainability, agility and
resilience of the European machinery manufacturing companies.
AUTO-TWIN addresses the technological shortcomings and economic liability
of the current system-engineering model.
DaCapo aims at improving the adoption of CE strategies along the value
chains and products lifecycles through AI-based apps, process/product DT.

7. Vienna, 12-13 June, 2023 | #FIWARESummit www.fiware.org
Sustainable Value Networks Services: the example of
Collaborative intelligence based on a
cluster of Circular Digital Twins to
facilitate AI applications across the
entire circular value chain.
Circular TwAIn identifies three highly
significant sources of data and
information input to train the human-
AI applications:
1. The (de-)manufacturing process
2. The product to be de-
manufactured
3. The human operator

8. Vienna, 12-13 June, 2023 | #FIWARESummit www.fiware.org
Sustainable Value Networks Services: the example of
Align Industry 4.0
National
Initiatives Across Europe
Set Business &
Maturity Assessment
Intelligence Foundations
Consolidate Technical
Foundations and SME-
friendly Building Block
Catalogue
Legal & Data
Foundations for Access
to DS 4.0 Ecosystem

9. Vienna, 12-13 June, 2023 | #FIWARESummit www.fiware.org
Sustainable Value Networks in Manufacturing :: Conclusions
• Interesting for both discrete and process industry
• Interesting for both manufacturer and consumers
• Needed to achieve sustainability goals at ecosystem level (e.g. thanks to a joint effort
at value network level)
 Challenges and Approaches for a Common European Data Space in
Manufacturing (Slot 1)

10. Vienna, 12-13 June, 2023 | #FIWARESummit www.fiware.org
THE DATA IS OUT THERE

11. Vienna, 12-13 June, 2023 | #FIWARESummit www.fiware.org
Connecting Data Sharing and Interoperability
• Break the silos
• Cross-organization benefits
• Interoperability and Smart Data Models
 Combining NGSI-LD and SHACL (Slot 2)
Competition vs. Co-opetition

12. Vienna, 12-13 June, 2023 | #FIWARESummit www.fiware.org
Enabling Technologies for Manufacturing
• Digital vs. Physical
• More and more data
• AI to embed intelligence
 Cognitive Application Platform and self-X AI
tools (Slot 3)
 Worker Augmented Reality guidance (Slot 4)
 Role of TEF for Manufacturing (Slot 5)

13. Vienna, 12-13 June, 2023 | #FIWARESummit www.fiware.org
Agenda for today
09:08 – 09:18 Challenges and Approaches for a Common European Data Space in
Manufacturing – Roland S. Sommer, Director General, Association Industry 4.0 AT
09:18 – 09:28 Combining NGSI-LD and SHACL: A Foundation for Next Generation
Digital Process Twins in Manufacturing – Marcel Wagner, Software Architect, INTEL
09:28 – 09:38 Cognitive Application Platform and self-X AI tools: powered-by-
FIWARE solutions for the Process Industry – Daniel Gómez Martín, Industrial
Engineer, CARTIF
09:38 – 09:48 WARNING – Worker Augmented Reality guidaNce IN aGile production
shop floor – Federico D’Ambrosio, Researcher, INTELLIMECH
09:38 – 09:58 FIWARE and AI TEF for Manufacturing: a win-win game – Maria
Rossetti, Project Manager, MADE-CC
09:58 – 10:00 Closing & Remarks – Ernoe Kovacs and Angelo Marguglio

14. Vienna, 12-13 June, 2023 | #FIWARESummit www.fiware.org
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15. Vienna, Austria
12-13 June, 2023
#FIWARESummit
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