OBJECTIVES

Data sharing among manufacturing companies and with (service) providers will be increased by the deployment of two data spaces of the manufacturing industry, which will demonstrate how sharing industrial data improves company operations.

Manufacturing data spaces and their AI-based analytics and optimisation applications can influence company-internal processes as well as processes across organisations. On the basis of the preparatory actions (esp. EU DATA SP4CE3), the main objective is to deploy two operational data spaces across value chains in the manufacturing sector, which enable companies in different user roles (e.g. supplier, client, service provider) to interact with large amounts of industrial data across their organisational borders. The first data space will address agile supply chain management and execution across a large set of supply chain stakeholders, and the second one
dynamic asset management and predictive/prescriptive maintenance, unlocking deep industrial data for trustworthy and reliable value-added services by parties outside a production site, such as machine tool manufacturers and integrators, improving production line operations.

SCOPE

The action calls for the deployment of two operational data spaces of the manufacturing industry, building on the work and results of the preparatory actions. Both discrete manufacturing and process industry are envisaged. The projects should have sufficient activities to lead to sustainability at the end of the action, in line with the business plans and blueprints proposed in the preparatory actions mentioned above.

Such data spaces will offer a secure and trustworthy way of making data usable between supplier and user companies on the basis of voluntary agreements. ‘Embryonic’ data spaces that are used by a significant amount of manufacturing companies should be scaled up to a European level. Their data sharing shall be deepened, expanded, and enlarged with other organisations, and gradually integrated into the Data Space Technical Infrastructure. The data spaces for manufacturing must be operated and coordinated by companies, an industrial association or a non-profit organisation demonstrating their capacity to act as trustworthy data brokers and to
continue operations beyond the end of the action.

The actions need to target one of these two specific complementary data spaces for manufacturing:

• Performing agile supply chain management and execution by continuously monitoring and exchanging status data on e.g. purchase orders, sales orders, inventory levels, order progress, demand forecasts, use of raw materials, chemicals and energy and supply, etc. across the value chain. End users are different tiers in a supply chain (suppliers, OEMs, and customers).
• Carrying out dynamic asset management and predictive/prescriptive maintenance by continuously monitoring and exchanging data on machine status, breakdowns, downtimes, service orders, etc. End users are machine users, machine vendors, maintenance service providers, and remanufacturers.

In addition, the actions need to address the following mandatory activities:

• Bringing together relevant stakeholders to industrial data agreement(s) on design, reuse, recycling, and environmental impact and indicators for continuous monitoring and exchange of data on product performance and reuse, material content and origin, feedback to design, product recycling, product remanufacturing, etc. The work should demonstrate data-based sustainable business models and the benefits of data sharing for the organisations participating in the value chains.
• Carrying out further actions needed to effectively track and report resource use (e.g. CO2) from a manufacturer’s perspective in going forward. Actions should preferably target data sharing for circularity in line with the Circular Economy Action plan (COM(2020) 98 final).

The actions for the deployment of these two data spaces for manufacturing will have to gradually make use and be in full compliance with the European Data Spaces Technical Framework. They will test and can profit from the smart cloud-to-edge middleware platform and tools that will be developed under topic ”DIGITAL-2022-CLOUD-AI-03-PILOTS-CLOUD-SERVICES - Large-scale pilots for cloud-to-edge based service solutions”. They will also have to coordinate and collaborate with other projects participating in the deployment of the data space, the Data Spaces Support Centre and the governance body identified by the preparatory action EU DATA SP4CE.
This coordination shall lead to the integration of existing standards and ensure interoperability and portability across infrastructure, applications and data.

Furthermore, the actions implementing the Data Spaces for Manufacturing are encouraged to cooperate with the European Digital Innovation Hubs for a broad uptake by the industry as well as the Testing and Experimentation Facility for Manufacturing to define European test and training data sets and to provide support in their establishment.

OUTCOMES AND DELIVERABLES

The two selected actions will each deploy a data space for the manufacturing industry at scale, continuing to be available after the end of the project, that will build on and be integrated with the data space technical infrastructure, delivering industrial data sharing among manufacturing companies and with (service) providers, thanks to agreements on common rules for access to data and fair compensation. The solutions must be characterized by a high degree of user-orientation in terms of trustworthiness, data sovereignty of the companies and manageability. Particularly SMEs will benefit from larger sets of industrial data to broaden their offers in terms of products and services, with the support of the European Digital Innovation Hubs.

Actions will address one of the following expected outcomes:

• Supply chain operations are more flexible, circular, effective and efficient, with a higher degree of managed inventory levels, more timely deliveries between organisations, better resilience to interruptions of delivery channels, and enhanced cost controls.
• Asset management and maintenance operations demonstrate higher performance, with better insight on asset criticality, reduced overall downtimes and maintenance costs, extended machine usage periods, and new service models.

As part of the actions addressing one of the expected outcomes above, the organisation(s) operating the data spaces will deliver good practices for data sharing agreements such as code of conduct and contract template enabling such a degree of trust that brings together a sizeable number of manufacturing companies.

Furthermore, stakeholders in these actions will agree on approaches and explore ideas for circularity, on how to improve design, reuse, repair, remanufacturing, recycling, and environmental impact by data sharing and demonstrate benefits of the first generation of the product passports for all involved stakeholders as well as for sustainability. Interoperability of data within this data space will be designed such that cross-sectoral interoperability can be easily achieved in the future.

To ensure a balanced portfolio covering all envisaged data spaces for manufacturing, grants will be awarded to actions not only in order of ranking but also to at least one action per expected outcome, provided that the applications attain all thresholds. The EU estimates that an EU contribution of around EUR 8 million would allow these outcomes to be addressed appropriately. Nonetheless, this does not preclude submission and selection of a proposal requesting different amounts.

KPIs TO MEASURE OUTCOMES AND DELIVERABLES 

• Percentage increase in number of organisations participating in the Data Space based on shared governance since project start
• Number, and geographic distribution, of connected data providers offering data sets based on the standards and conditions identified by the network.
• Data volume shared in the network, volume of data effectively used multiple times
• Number of data generating assets effectively connected to data spaces
• Percentage of data for which metrics for data quality are applied
• Case studies of demonstrated Return on Investments (RoI) of data space deployment
• Level of adoption of models incentivising businesses (financially and nonfinancially) to constantly keep data up-to-date
• Number of data space service providers offering analytics based on the solutions identified by the network.
• Share of supplier/customer interactions having undergone automation
• Share of SMEs among data providers and data users

The consortium should also propose relevant indicators (including industry and service relevant KPIs) for measuring the expansion of usage and impact of the data space.

Indicators should be accompanied by target values.

TARGETED STAKEHOLDERS

Consortium should include at least suppliers and users as well as service providers, any other organisation (such as data brokers, data stewards, data integrators) participating in data interoperability activities and organisations

TYPE OF ACTION AND FUNDING RATE

SME Support Actions — 50% and 75% (for SMEs) funding rate

SPECIFIC TOPIC CONDITIONS

• For this topic, security restrictions under Article 12(6) of the Digital Europe Regulation apply (see sections 6 and 10 and Annex 2)
• For this topic, multi-beneficiary applications are mandatory and specific conditions for the consortium composition apply (see section 6)
• For this topic, following reimbursement option for equipment costs applies: depreciation and full cost for listed equipment (see section 10)
• For this topic, first exploitation obligations apply (see section 10)]
• The following parts of the award criteria in section 9 are exceptionally NOT applicable for this topic:
  • extent to which the proposal can overcome financial obstacles such as
    the lack of market finance