For this Open call, we are looking for end-user SMEs and mid-caps interested in developing and implementing digital twin technology. Up to 11 manufacturing SMEs and midcaps will be selected to receive up to €90 000 as a lump sum to cover the costs to deploy and implement technology and systems applicable to digital twins for manufacturing together with technical mentorship to support the experiment in each phase of its implementation from user requirements to design specification.

The ideal use case should use digital twin technology for one or several of the following purposes:

• Virtual Design: Model-based system engineering, including analysis and design, ensuring that requirements are met and providing for seamless integration, test, verification and validation.
• Customer Engagement: Interactive display of the system and its capabilities, for customers to understand how it meets their needs and how they will use it.
• Commissioning: Checking the on-site implementation of a system against its design as captured in the digital twin to detect commissioning faults or anomalies.
• Feedback to Engineering: Capturing usage characteristics with the digital twin to inform engineering of needs to change designs, or for future designs, or of operational risks.
• Monitoring: Monitoring of a system’s operation by the digital twin that is then able to, e.g., detect anomalies, performance degradation, etc.
• Optimisation & Best Quality: Process control with the digital twin to optimise a systems operation for best performance and efficiency.
• Scheduling: Organisation of workflows based on actual data and insights provided by the digital twin.
• Diagnosis: Investigation of the cause or nature of a fault condition, situation, or problem in the physical system by reasoning on live data within the digital twin.
• Preventive Maintenance: Maintenance and service of a physical system that lessens the likelihood of failures based on the observed and inferred system state as visible in the digital twin.
• Smart Logistics: Logistic processes that adapt to live data of needs and options as visible in the digital twin.
• Smart Systems: Systems that adapt to their dynamic environment, state, or tasks and potentially learn how to do that best. The digital twin is then a core part of the system’s control.

The proposed use cases must increase the digital maturity of the end user, and the project should eventually provide clear lessons learned to be shared with the manufacturing community in Europe.