A Novel Model Adaption Approach for intelligent Digital Twins of Modular Production Systems

Dittler, Daniel; Lierhammer, Peter; Braun, Dominik; Müller, Timo; Jazdi, Nasser; Weyrich, Michael

doi:10.1109/etfa54631.2023.10275384

Cited by 4 publications

(1 citation statement)

References 28 publications

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“…Recent advancements in autonomous manufacturing have extensively utilized digital twin technologies to enhance operational efficiencies and facilitate real-time decisionmaking. Specifically, studies have demonstrated various facets of digital twin applications: The authors of [4] presented methodologies for deriving project-specific digital twins tailored to industrial automation needs, focusing on modular integration and technology adaptability. An early implementation of digital twin technology was showcased in [5], where educational setups leveraged cloud computing and 5G networks for process automation.…”

Section: Related Work 21 Autonomous Manufacturingmentioning

confidence: 99%

Enhancing Industrial Process Control: Integrating Intelligent Digital Twin Technology with Proportional-Integral-Derivative Regulators

Dapkute,

Siozinys,

Jonaitis

et al. 2024

Machines

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This paper explores the integration of intelligent digital twin technology with PID regulators in industrial process control utilizing smart meter data. It presents a novel approach involving the creation of mathematical models to simulate real-time system behavior, thereby enhancing the PID control loop. The focus is on the development of specialized IT infrastructure to support this integration, which includes data acquisition, processing, and control optimization. This integration aims to not only improve control system efficiency but also introduce a robust predictive maintenance framework, offering significant benefits across a wide range of industrial applications.

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Section: Related Work 21 Autonomous Manufacturingmentioning

confidence: 99%