A digital twin of a manufacturing system is a digital copy of the physical manufacturing system that consists of various digital models at multiple scales and levels. Digital twins that communicate with their physical counterparts throughout their lifecycle are the basis for data-driven factories. The problem with developing digital models that form the digital twin is that they operate with large amounts of heterogeneous data. Since the models represent simplifications of the physical world, managing the heterogeneous data and linking the data with the digital twin represent a challenge. The paper proposes a five-step approach to planning data-driven digital twins of manufacturing systems and their processes. The approach guides the user from breaking down the system and the underlying building blocks of the processes into four groups. The development of a digital model includes predefined necessary parameters that allow a digital model connecting with a real manufacturing system. The connection enables the control of the real manufacturing system and allows the creation of the digital twin. Presentation and visualization of a system functioning based on the digital twin for different participants is presented in the last step. The suitability of the approach for the industrial environment is illustrated using the case study of planning the digital twin for material logistics of the manufacturing system.
This paper presents a novel approach to implement manufacturing nodes using the combined strength of digital twins, holons, and digital agents. Manufacturing nodes are based on holon theory and present a universal manufacturing platform that consists of cyber-physical systems (CPS) with an integrated digital twin, digital agent, databases and various communication protocols. The manufacturing node network is controlled globally using the global digital twin of logistics process and locally using the local nodes and local digital agents, digital twins and information shared by the node network. The main objective of this research was to develop and test a new concept of distributed system modelling and distributed system control for easy implementation of distributed manufacturing nodes in a smart factory concept.
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