From digital twins to supply chain ecosystems

We extend the recently developed intelligent digital twin (iDT) framework toward digital supply ecosystem notion. Digital ecosystem of a supply chain is a set of digital technologies, AI-based knowledge management systems, and data spaces and platforms enabling digital twins and simulation models. Digital twins are generated and adapted in digital ecosystems representing physical systems and objects in a data- and knowledge-driven manner. Specifically, we elaborate on how simulation, digital technologies and artificial intelligence (AI) can be combined to achieve a principally new quality of modeling and decision-making support in supply chain management. Digital ecosystems can be instrumental in building the capability for automatic generation and adaptation of models. That is, instead of having an expert construct a model based solely on their knowledge of the system, it involves enabling the system to build its model and, more importantly, adapt this model dynamically based on evolving knowledge (e.g., using a combination of ontologies and generative AI) and constantly updated data. Moreover, ecosystems help not only in building models but also in automatically generating scenarios for modeling (e.g., disruption and crisis scenarios). Essentially, it encompasses a combination of observation (i.e., object identification) and control tasks. We contextualize the application of digital ecosystems using examples of supply chain resilience, ripple effect, and stress testing.