A Digital Twin and Data Spaces framework towards Resilient Manufacturing Value Chains
Emmanouil Bakopoulos, Kostantinos Sipsas, Nikolaos Nikolakis, Kosmas Alexopoulos
Abstract
Due to the fact that uncertainties and disruptions are increasing because of the complexity of the supply chains, resilience has become a very important and imperative aspect for modern manufacturing industries. The ability to overcome challenging circumstances without significant additional costs is referred to as resilience. Digital technologies are considered as key enablers for manufacturers to achieve resilience in their manufacturing systems either in shopfloor or in value chain level. This work presents the framework of an information system for implementing Resilient Manufacturing value chains. The objective is to achieve resilience by applying the framework which leverages on data space technology, such as Gaia-X or International Data Space (IDS), and the Asset Administration Shell (AAS), where AAS supports the implementation of Digital Twins. Moreover, this work discusses the integration, within the proposed architecture, of two services namely Resilience Assessment and Reconfiguration Services. The architecture is validated in an industrial production environment from the steel industry. Finally, a discussion on existing challenges, limitations and future potentials takes place.