Abstract
The production sector has faced many difficulties in taking full advantage of opportunities found in other web application domains. Production research has focused on sophisticated mathematical models ranging from molecular materials modeling to efficient production control to inter-company supply network logistics. Often, these models have no closed-form solutions; this led to intense simulation research for individual modeling viewpoints, often labeled “Digital Twins”.
However, the complexity of the overall system precludes Digital Twins covering more than just a few system perspectives, especially if near-realtime performance is required. Moreover, the wide variety of individual situations and behaviors is usually captured only as statistical uncertainty. In order to achieve better performance and more context adaptation, the interdisciplinary research cluster “Internet of Production” at RWTH Aachen University is exploring the concept of “Digital Shadows”. Digital Shadows can be understood as compact views on dynamic processes, usually combining condensed measurement data with highly efficient simplified mathematical models. In this exploratory paper, we argue based on a couple of initial case studies that Digital Shadows are not just valuable carriers of deep engineering knowledge but due to their small size also help in reducing network congestion and enabling edge computing. These properties could make Digital Shadows an interesting solution to address resilience in other information-intensive dynamic systems.