#5081. Developing sensor signal-based digital twins for intelligent machine tools

July 2026publication date
Proposal available till 17-05-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Industrial and Manufacturing Engineering;
Information Systems and Management;
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Abstract:
Digital twins can assist machine tools in performing their monitoring and troubleshooting tasks autonomously from the context of smart manufacturing. The twin must (1) machine-learn the required knowledge from the historical sensor signal datasets, (2) seamlessly interact with the real-time sensor signals, (3) handle the semantically annotated datasets stored in clouds, and (4) accommodate the data transmission delay. The development of such twins has not yet been studied in detail. This study fills this gap by addressing sensor signal-based digital twin development for intelligent machine tools. Two computerized systems denoted as Digital Twin Construction System (DTCS) and Digital Twin Adaptation System (DTAS) are proposed to construct and adapt the twin, respectively. The modular architectures of the proposed DTCS and DTAS are presented in detail. The systems are also developed using a Java™-based platform. Milling torque signals are used as an example to demonstrate the efficacy of DTCS and DTAS.
Keywords:
Cyber-physical systems; Digital twin; Machine tool; Monitoring; Sensor signal

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