%0 Conference Paper %1 10.1007/978-3-031-74482-2_25 %A Chen, Shengjian %A Watter, Pascal %A Klingel, Lars %A Neubauer, Michael %A Verl, Alexander %B Flexible Automation and Intelligent Manufacturing: Manufacturing Innovation and Preparedness for the Changing World Order %C Cham %D 2024 %E Wang, Yi-Chi %E Chan, Siu Hang %E Wang, Zih-Huei %I Springer Nature Switzerland %K CNC %P 218--225 %T Utilizing Operational-Parallel Real-Time Simulation to Monitor and Optimize Workpiece Quality on CNC Machines %X Digital twins have a wide range of applications throughout the life cycle of computerized numerical controlled (CNC) machines. One particular manifestation of digital twins is the creation of models derived from virtual commissioning. These models actively accompany a physical machine throughout the engineering phase, but are typically discarded afterward. The objective of this study is to demonstrate the effectiveness of operation-parallel real-time simulation using virtual commissioning models for the early detection and elimination of defects in workpieces produced by CNC machines. The simulation model interfaces directly with the control drive, producing a virtual workpiece simultaneously with the actual manufacturing process in real-time, thus enabling necessary optimizations. Simultaneously, a virtual comparative model operates in the background to detect errors in the workpiece during runtime. This approach provides the advantage of eliminating the requirement for post-production quality inspections since the operational-parallel simulation conducts the inspection function. In addition, defects in the workpiece can be detected early so that the machine can be stopped in the event of a tolerance violation. At last, a framework is proposed to enable a knowledge-based model derived from identified defects. This framework can identify errors in early engineering stages, including the CAM planning phase, by using the knowledge from the production phase. %@ 978-3-031-74482-2

@inproceedings{10.1007/978-3-031-74482-2_25, abstract = {Digital twins have a wide range of applications throughout the life cycle of computerized numerical controlled (CNC) machines. One particular manifestation of digital twins is the creation of models derived from virtual commissioning. These models actively accompany a physical machine throughout the engineering phase, but are typically discarded afterward. The objective of this study is to demonstrate the effectiveness of operation-parallel real-time simulation using virtual commissioning models for the early detection and elimination of defects in workpieces produced by CNC machines. The simulation model interfaces directly with the control drive, producing a virtual workpiece simultaneously with the actual manufacturing process in real-time, thus enabling necessary optimizations. Simultaneously, a virtual comparative model operates in the background to detect errors in the workpiece during runtime. This approach provides the advantage of eliminating the requirement for post-production quality inspections since the operational-parallel simulation conducts the inspection function. In addition, defects in the workpiece can be detected early so that the machine can be stopped in the event of a tolerance violation. At last, a framework is proposed to enable a knowledge-based model derived from identified defects. This framework can identify errors in early engineering stages, including the CAM planning phase, by using the knowledge from the production phase.}, added-at = {2025-01-09T15:22:06.000+0100}, address = {Cham}, author = {Chen, Shengjian and Watter, Pascal and Klingel, Lars and Neubauer, Michael and Verl, Alexander}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/20161067d957304283c667aff62a65895/isw-bibliothek}, booktitle = {Flexible Automation and Intelligent Manufacturing: Manufacturing Innovation and Preparedness for the Changing World Order}, editor = {Wang, Yi-Chi and Chan, Siu Hang and Wang, Zih-Huei}, interhash = {9110af9144518363a952867240e00058}, intrahash = {0161067d957304283c667aff62a65895}, isbn = {978-3-031-74482-2}, keywords = {CNC}, pages = {218--225}, publisher = {Springer Nature Switzerland}, timestamp = {2025-01-09T15:22:06.000+0100}, title = {Utilizing Operational-Parallel Real-Time Simulation to Monitor and Optimize Workpiece Quality on CNC Machines}, year = 2024 }