A data- and knowledge-driven framework for digital twin manufacturing cell

Abstract

Intelligent manufacturing is regarded as the next generation manufacturing mode with powerful learning and cognitive capacities enabled by new generation information technologies such as Internet of Things, big data analytics, edge computing and artificial intelligence. To provide an insight into intelligent manufacturing, this paper takes autonomous manufacturing cell as implementation scenario and proposes a data- and knowledge-driven framework for digital twin manufacturing cell (DTMC), which could support autonomous manufacturing by an intelligent perceiving, simulating, understanding, predicting, optimizing and controlling strategy. In addition, three key enabling technologies including digital twin model, dynamic knowledge bases and knowledge-based intelligent skills for supporting the above strategy are analyzed. Then, the implementing methods of DTMC are introduced through a thus constructed digital twin robot, and the usage of data and knowledge for supporting the automous operations of DTMC is also discussed. Finally, benefits of DTMC in smart product-service systems (PSS) and its current challenges are summarized.