Manufacturing as a Service and the DATA/AI backbone challenge
Manufacturing-as-a-Service (MaaS) is a business model that extends the principles of the “as-a-service” paradigm to the manufacturing industry. It involves providing manufacturing capabilities and services on a subscription or pay-per-use basis, similar to how cloud computing or software-as-a-service (SaaS) models work. In MaaS, a company or individual can access and utilize manufacturing resources and expertise without having to invest in or operate their own manufacturing facilities. Manufacturing servitisation in resilient supply chains implies advanced digitalisation of the manufacturing business processes as well as the availability of decentralised Data– and Software-as-a-Service infrastructures. More recently, advanced agentic AI applications for demand-offer matching, multi-criteria selection of suppliers, and supply chain resilience optimisation have demonstrated their validity and economic impact on several different manufacturing sectors and value chains.
In 2023, the Made in Europe Partnership launched a Horizon Europe topic entitled “Achieving resiliency in value networks through modelling and Manufacturing as a Service” (HORIZON-CL4-2023-TWIN-TRANSITION-01-07). Eight Research and Innovation Actions were funded under the coordination of the MASTT2040 CSA, and some of them (MAASive, M4ESTRO, ACCURATE and NARRATE) are nearing their final stage and are ready to present their methodological and technological results, their industrial pilots and the lessons learned.
Session concept
The “Manufacturing as a Service and the DATA/AI Backbone Challenge” session, sponsored by the MAASive project, and jointly featuring the participation of its sister projects M4ESTRO, ACCURATE, and NARRATE, is structured as a multi-project debate organised to discuss a coordinated overview of the latest developments and opportunities in Manufacturing-as-a-Service, while spanning different technological approaches and perspectives, and showcasing industrial validation cases that provide tangible evidence of impact and readiness for adoption, as well as insights into interoperability challenges and scalability pathways for Data/AI-driven Manufacturing-as-a-Service ecosystems.
The aim is to highlight opportunities and foster engagement around the future evolution of MaaS in Europe, contributing to the long-term vision of European manufacturing competitiveness towards 2040.
Agenda
Brief introduction (Sergio Gusmeroli and Davide Dalle Carbonare | BDVA Smart Manufacturing Industry Group)
Context – MaaS vision and state of play.
- Which is the role of Data Infrastructures (e.g. Data Spaces) and AI Infrastructures (e.g. AI TEF and AI Factories) in the implementation of MaaS solutions?
- Which is the experience gained from the four projects?
- Which are the opportunities and the challenges offered by Data / AI backbone infrastructures?
- How easy was it to implement Data / AI infrastructures in Industrial cases?
- Which were the benefits and the challenges?
- Lessons learned for future massive implementation of MaaS in Manufacturing Industry.
Project presentations
Key results and industrial testimonials
Format of 15′ per project (project presentation + Data/AI implementation + 1-2 cases)
- MAASive “Insights from implementing an integrated resilience and disruption response framework based on MaaS in the MAASIVE project.”
presented by Thomas Ditlev Brunø, AALBORG UNIVERSITET - M4ESTRO: “Resilient MaaS in Action – Sovereign Data, Explainable AI, Industrial Supply Chains”
presented by Konstantina Tsioli, CORE INNOVATION - ACCURATE: “Interoperability for Manufacturing-as-a-Service: Connecting Data Spaces, Digital Marketplaces and Decision-Making”
presented by Valeria Borodin, IMT ATLANTIQUE and Thomas Komenda, DeltaDAO - NARRATE: “Manufacturing as a Service Meets Industrial Resilience: An AI-Driven Platform for Risk Detection, Explainable Decision-Making and Response Orchestration.”
presented by Jesús Ávila Molina, NUNSYS
Panel discussion moderated br Sergio Gusmeroli
Cross-project discussion on challenges, interoperability, scalability, and future adoption of MaaS in Europe toward 2040
- Sharing Data: Which are the opportunities and the main obstacles? Are DS technologies simplifying the data sharing process
- Which is the role of AI (agentic AI) in the discovery / selection and engagement of new suppliers? How does it depend on factors (trust brand personal aspects) which cannot be modelled in an AI Agentic application? Human decision?
- The industrial cases present which benefits they gained from the MaaS experimentation and how to address now replicability and scalability. Critical mass of data is needed? Full integration with SCM CRM legacy systems.
- Which sectors / applications are in your opinion most suitable for a massive implementation of the MaaS principles? At design time (a one-of-a-kind order), at manufacturing time (disruptions in the value chain, high volume production)?
Project groups
