An industrial data-spaces framework for resilient manufacturing value chains

Abstract

Manufacturing industries continuously face the challenge of delivering high-quality products under high production rates while minimizing non-value adding activities. The recent COVID-19 pandemic has caused manufacturers to rethink and reassess their global supply chains and the flexibility of their production sites. Resilience means the ability to withstand difficult situations without incurring significant extra costs. The deficiencies can be attributed largely to the lack of efficient ways for trusted data sharing among the value chain stakeholders without interoperability barriers. There is a need to be able to determine when such changes lead to deterministic-chaotic behavior with far reaching consequences. This work presents a framework to support production networks' reconfiguration for resilient manufacturing value chains. The proposed concept utilizes platform-based manufacturing that builds on the concept of dataspace and its reference implementations of Gaia-X and IDS for data-sharing in the horizontal supply chain and the Asset Administration Shell (AAS) for implementing intra-factory reconfiguration practices. Moreover, the proposed framework considers the Digital Twin of the value-adding network as a key enabling technology to achieve reconfiguration of production systems and networks. The concept has been projected upon an industrial case in order to validate its potential.