Digital Twin Development and Operation of a Flexible Manufacturing Cell using ISO 23247

Abstract

Digital twins are representations of real-world systems in the digital world, relying on physical system data to optimise, manipulate, detect, and interact. The requirements of digital twins diverge depending on the application in focus. The complexity ranges from simple to highly complex use cases, which increases setup time and reduces maintainability. Therefore, different representations and views of the digital twin are necessary, e.g., file type conversions or abstractions of geometry. Standards that try to solve these problems are ISO 21597, by providing containerisation and linkage of data, and ITU-T Y.3090 and ISO 23247, by providing frameworks to support the creation process of digital twins. Based on these standards, this paper aims to enable a holistic view of digital twin applications in flexible manufacturing cells to reduce the implementation effort when the system is installed or changes. We identify a digital twin's most relevant features, parameters, and assets. This feature set is categorised regarding the frequency of changes. The main observable manufacturing elements are machine tools, robots, peripheral devices like autonomous mobile robots (AMRs), manufacturing utilities like tools, and processes. Various information systems depend on or interact with these manufacturing cells, e.g., CAM, PLM, MES, tool management, fleet control, and cell control. While applying the framework of ISO 23247 to a flexible manufacturing cell, we found that life cycle changes are only considered for products and not for the digital twin itself. Therefore we try to emphasise life cycle changes by linking the manufacturing cell to a life cycle meta-layer, simplifying the design, deployment, and updates of digital twin applications. This linkage remains valid through changes, reducing application maintenance effort by allowing re-instantiation of the applications. Therefore, a multidimensional representation of the physical layer can address rapidly changing real-time data to hardly changing life cycle information.