Digital Twins (DTs) can be used for optimization, analysis and adaptation of complex engineered systems, in particular after these systems have been deployed. DTs make full use of both historical knowledge and of streaming data from sensors. DTs have been given numerous (distinct) definitions and descriptions in the literature. There is no consensus on terminology, nor a comprehensive description of workflows nor architectures. Following Multi-Paradigm Modelling principles, this paper proposes to explicitly model construction and use workflows of DTs as well as their architectures. We apply the concepts of variability (also known as product family) modeling, in particular to DT workflow and architecture. This allows for the de-/re-construction of the different DT variants in a principled, reproducible and partially automatable manner. To illustrate our ideas, two small use cases are discussed: a line-following robot (representative for an Automated Guided Vehicle) and an incubator (r epresentative for an Industrial Convection Oven). The use cases focus on important systems in an industrial context
Original language
English
Title of host publication
Proceedings of the 2nd International Conference on Innovative Intelligent Industrial Production and Logistics
