Project description
Solving manufacturing challenges with digital twins
In modern manufacturing, traditional models face challenges of inflexibility and susceptibility to disruptions. These issues stem from rigid structures and insufficient adaptability to dynamic market demands. Moreover, the lack of trust among stakeholders hinders collaboration and resource sharing, impeding efficiency. In this context, the EU-funded Tec4MaaSEs project will develop a network of trustworthy and cognitive digital twins, enabling collaborative work within value networks. This facilitates manufacturing as a service, or MaaS, where production is offered as a service. The project’s comprehensive framework enhances resilience and sustainability through continuous evaluation, addressing supply and demand variations. Flexible adaptation, innovative business models and a governance framework ensure trust, resource sharing and coordination.
Objective
Tech4MaaSEs derives inspiration from industrial challenges, scientific inquiries, and societal needs. At its core, Tech4MaaSEs develops a network of Digital Twins that possess both trustworthiness and cognition, allowing them to work collaboratively within a distributed value network. This network of Digital Twins is a key enabler for Manufacturing-as-a-Service (MaaS), where production and anufacturing are offered as a service. Tec4MaaSEs provides a comprehensive DT-based framework for value networks, which enables greater resilience and sustainability across the entire value network with continuous evaluation and monitoring of performance through a multilevel balanced scorecard system. Highly configurable, the solution is able to respond to the varying supply and demand of individual stakeholders. This flexibility makes it possible to evaluate alternatives and react appropriately, while improving the understanding of the impact of external disruptions. The project will deliver innovative business models that ensure adequate level of trust among the involved stakeholders, and flexible adaptation of production capabilities, sharing of resources and assets and coordination of individual value creation activities in the value network. A complementary Governance Framework improves oversight and control of the underlying industrial operations. Governance is declined along three dimensions: Business Governance, for operational and procedural aspects and applicable resource sharing strategies. Data Governance, addressing confidentiality, data sharing polices, data authorization/ownership/ etc, and AI models governance - how human centred-AI models ensure trustworthiness and AI explainability. The solution will be validated in three real value networks demonstrating the improved resilience and sustainability of the solution.
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HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
47822 Santarcangelo Di Romagna
Italy