Content area

Abstract

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.

Details

1009240
Title
A Bidirectional Digital Twin System for Adaptive Manufacturing
Volume
9
Issue
12
First page
400
Number of pages
24
Publication year
2025
Publication date
2025
Publisher
MDPI AG
Place of publication
Basel
Country of publication
Switzerland
e-ISSN
25044494
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-12-04
Milestone dates
2025-10-28 (Received); 2025-11-28 (Accepted)
Publication history
 
 
   First posting date
04 Dec 2025
ProQuest document ID
3286310104
Document URL
https://www.proquest.com/scholarly-journals/bidirectional-digital-twin-system-adaptive/docview/3286310104/se-2?accountid=208611
Copyright
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-12-24
Database
ProQuest One Academic