A Bidirectional Digital Twin System for Adaptive Manufacturing
में बचाया:
| में प्रकाशित: | Journal of Manufacturing and Materials Processing vol. 9, no. 12 (2025), p. 400-423 |
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| मुख्य लेखक: | |
| अन्य लेखक: | , |
| प्रकाशित: |
MDPI AG
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| विषय: | |
| ऑनलाइन पहुंच: | Citation/Abstract Full Text + Graphics Full Text - PDF |
| टैग: |
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MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 3286310104 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2504-4494 | ||
| 024 | 7 | |a 10.3390/jmmp9120400 |2 doi | |
| 035 | |a 3286310104 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a Heide, Klaas Maximilian | |
| 245 | 1 | |a A Bidirectional Digital Twin System for Adaptive Manufacturing | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Digital Twin Systems (DTSs) are increasingly recognized as enablers of data-driven manufacturing, yet many implementations remain limited to monitoring or visualization without closed-loop control. This study presents a fully integrated DTS for CNC milling that emphasizes real-time bidirectional coupling between a real machine and a virtual counterpart as well as the use of machine-native signals. The architecture comprises a physical space defined by a five-axis machining center, a virtual space implemented via a dexel-based technological simulation environment, and a digital thread for continuous data exchange between those. A full-factorial simulation study investigated the influence of dexel density and cycle time on engagement accuracy and runtime, yielding an optimal configuration that minimizes discretization errors while maintaining real-time feasibility. Latency measurements confirmed a mean response time of 34.2 ms, supporting process-parallel decision-making. Two application scenarios in orthopedic implant milling validated the DTS: process force monitoring enabled an automatic machine halt within 28 ms of anomaly detection, while adaptive feed rate control reduced predicted form error by 20 µm. These findings demonstrate that the DTS extends beyond passive monitoring by actively intervening in machining processes; enhancing process reliability and part quality; and establishing a foundation for scalable, interpretable digital twins in regulated manufacturing. | |
| 653 | |a Accuracy | ||
| 653 | |a Data exchange | ||
| 653 | |a Adaptability | ||
| 653 | |a Quality control | ||
| 653 | |a Closed loops | ||
| 653 | |a Machine tools | ||
| 653 | |a Predictive control | ||
| 653 | |a Data processing | ||
| 653 | |a Aerospace industry | ||
| 653 | |a Production planning | ||
| 653 | |a Manufacturing | ||
| 653 | |a Monitoring | ||
| 653 | |a Turbines | ||
| 653 | |a Simulation | ||
| 653 | |a Adaptive systems | ||
| 653 | |a Physics | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Digital twins | ||
| 653 | |a Milling (machining) | ||
| 653 | |a Sensors | ||
| 653 | |a Decision making | ||
| 653 | |a Orthopaedic implants | ||
| 653 | |a Process controls | ||
| 653 | |a Cycle time | ||
| 653 | |a Anomalies | ||
| 653 | |a Feed rate | ||
| 653 | |a Machining centres | ||
| 653 | |a Real time | ||
| 653 | |a Industry 4.0 | ||
| 653 | |a Feedback control | ||
| 653 | |a Orthopedics | ||
| 653 | |a Run time (computers) | ||
| 700 | 1 | |a Denkena Berend | |
| 700 | 1 | |a Winkler, Martin | |
| 773 | 0 | |t Journal of Manufacturing and Materials Processing |g vol. 9, no. 12 (2025), p. 400-423 | |
| 786 | 0 | |d ProQuest |t ABI/INFORM Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3286310104/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3286310104/fulltextwithgraphics/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3286310104/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |