Autonomous, context-aware, adaptive Digital Twins-State of the art and roadmap

Digital Twins are an important concept in the comprehensive digital representation of manufacturing assets, products, and other resources, comprising their design and configuration, state, and behaviour. Digital Twins provide information about and services based on their physical counterpart's current condi-tion, history and predicted future. They are the building blocks of a vision of future Digital Factories where stakeholders collaborate via the information Digital Twins provide about physical assets in the factory and throughout the product lifecycle. Digital Twins may also contribute to more flexible and resilient Dig-ital Factories. To achieve this, Digital Twins will need to evolve from today's expert-centric tools towards active entities which extend the capabilities of their physical counterparts. Required features include sensing and processing their environment and situation, pro-actively communicating with each other, taking decisions towards their own or cooperative goals, and adapting themselves and their physical counterparts to achieve those goals. Future Digital Twins will need to be context-aware, autonomous, and adaptive. This paper aims to establish a roadmap for this evolution. It sets the scene by proposing a working definition of Digital Twins and examines the state-of-the-art in the three topics in their relation to DTs. It then elaborates potentials for each topic mapped against the working definition, to finally iden-tify research gaps allowing for the definition of a roadmap towards the full realisation of autonomous, context-aware, adaptive Digital Twins as building blocks of tomorrow's Digital Factories. (c) 2021 Elsevier B.V. All rights reserved.