Details
| Original language | English |
|---|---|
| Pages (from-to) | 342-347 |
| Number of pages | 6 |
| Journal | Procedia CIRP |
| Volume | 126 |
| Early online date | 9 Oct 2024 |
| Publication status | Published - 2024 |
| Event | 17th CIRP Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME 2023 - Naples, Italy Duration: 12 Jul 2023 → 14 Jul 2023 |
Abstract
In milling processes, collisions lead to cost-intensive machine damages and long-term maintenance downtimes. Collisions tests are essential in CAD/CAM planning when it comes to small batch sizes e.g. for aerospace parts. Currently, experimental tests are carried out based on the nominal clamping situation and CAD data. Clamping errors, probing errors and particularly incorrect tool lengths are thereby not considered. For this reason, a concept for a sensor-based collision detection system is presented. The integration of an automatic image recognition in combination with a material removal simulation enables an accuracy of 96.87 % in collision detection for three defined reference workpieces.
Keywords
- CNC automation, collision avoidance, collision detection, laser scanning, object detection, process simulation
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Engineering(all)
- Industrial and Manufacturing Engineering
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In: Procedia CIRP, Vol. 126, 2024, p. 342-347.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Simulation-based collision detection for CNC machining using sensor-based image recognition
AU - Denkena, B.
AU - Wichmann, M.
AU - Malek, T.
AU - Raeker, R.
N1 - Publisher Copyright: © 2024 Elsevier B.V.. All rights reserved.
PY - 2024
Y1 - 2024
N2 - In milling processes, collisions lead to cost-intensive machine damages and long-term maintenance downtimes. Collisions tests are essential in CAD/CAM planning when it comes to small batch sizes e.g. for aerospace parts. Currently, experimental tests are carried out based on the nominal clamping situation and CAD data. Clamping errors, probing errors and particularly incorrect tool lengths are thereby not considered. For this reason, a concept for a sensor-based collision detection system is presented. The integration of an automatic image recognition in combination with a material removal simulation enables an accuracy of 96.87 % in collision detection for three defined reference workpieces.
AB - In milling processes, collisions lead to cost-intensive machine damages and long-term maintenance downtimes. Collisions tests are essential in CAD/CAM planning when it comes to small batch sizes e.g. for aerospace parts. Currently, experimental tests are carried out based on the nominal clamping situation and CAD data. Clamping errors, probing errors and particularly incorrect tool lengths are thereby not considered. For this reason, a concept for a sensor-based collision detection system is presented. The integration of an automatic image recognition in combination with a material removal simulation enables an accuracy of 96.87 % in collision detection for three defined reference workpieces.
KW - CNC automation
KW - collision avoidance
KW - collision detection
KW - laser scanning
KW - object detection
KW - process simulation
UR - http://www.scopus.com/inward/record.url?scp=85208536953&partnerID=8YFLogxK
U2 - 10.1016/j.procir.2024.08.370
DO - 10.1016/j.procir.2024.08.370
M3 - Conference article
AN - SCOPUS:85208536953
VL - 126
SP - 342
EP - 347
JO - Procedia CIRP
JF - Procedia CIRP
SN - 2212-8271
T2 - 17th CIRP Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME 2023
Y2 - 12 July 2023 through 14 July 2023
ER -