Details
| Original language | English |
|---|---|
| Pages (from-to) | 193-198 |
| Number of pages | 6 |
| Journal | Procedia CIRP |
| Volume | 118 |
| Early online date | 18 Jul 2023 |
| Publication status | Published - 2023 |
| Event | 16th CIRP Conference on Intelligent Computation in Manufacturing Engineering 2022 - Naples, Italy Duration: 13 Jul 2022 → 15 Jul 2022 |
Abstract
Process and tool condition monitoring systems are a prerequisite for autonomous production. For online monitoring, it is the state of the art to use reference signals of correct processes to improve failure sensitivity and reduce false alarms. Transferring these reference signals from other machines economizes on teach-in processes and complex simulations. However, the varying behaviour of the two machines leads to differences that need to be considered for the transfer. This work aims to identify similarities and differences in the timing and positioning of multiple machines when executing identical machining instructions. A comparison of process signals quantifies similarities and differences among machines. Results describe differences between process sequences, rapid traverse speeds, rapid traverse paths, machining feed speeds, machining feed paths, tool engagement time, and the temporal alignment of signals. Differences primarily originated from different control parameters and strategies as well as physical drive limitations. During machining differences occurred most frequently when axes were accelerated. Differences accumulated over prolong periods of machining and eventually became relevant from the perspective of online monitoring.
Keywords
- knowledge transfer, machine tools, tool condition monitoring
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Engineering(all)
- Industrial and Manufacturing Engineering
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In: Procedia CIRP, Vol. 118, 2023, p. 193-198.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Identical NC-code on Different Machine Tools
T2 - 16th CIRP Conference on Intelligent Computation in Manufacturing Engineering 2022
AU - Denkena, Berend
AU - Bergmann, Benjamin
AU - Stiehl, Tobias H.
N1 - Funding Information: The authors acknowledge the financial support from the Federal Ministry for Economic Affairs and Climate Action of Germany (BMW K ) in the project IIP-Ecosphere (project number 01MK20006A).
PY - 2023
Y1 - 2023
N2 - Process and tool condition monitoring systems are a prerequisite for autonomous production. For online monitoring, it is the state of the art to use reference signals of correct processes to improve failure sensitivity and reduce false alarms. Transferring these reference signals from other machines economizes on teach-in processes and complex simulations. However, the varying behaviour of the two machines leads to differences that need to be considered for the transfer. This work aims to identify similarities and differences in the timing and positioning of multiple machines when executing identical machining instructions. A comparison of process signals quantifies similarities and differences among machines. Results describe differences between process sequences, rapid traverse speeds, rapid traverse paths, machining feed speeds, machining feed paths, tool engagement time, and the temporal alignment of signals. Differences primarily originated from different control parameters and strategies as well as physical drive limitations. During machining differences occurred most frequently when axes were accelerated. Differences accumulated over prolong periods of machining and eventually became relevant from the perspective of online monitoring.
AB - Process and tool condition monitoring systems are a prerequisite for autonomous production. For online monitoring, it is the state of the art to use reference signals of correct processes to improve failure sensitivity and reduce false alarms. Transferring these reference signals from other machines economizes on teach-in processes and complex simulations. However, the varying behaviour of the two machines leads to differences that need to be considered for the transfer. This work aims to identify similarities and differences in the timing and positioning of multiple machines when executing identical machining instructions. A comparison of process signals quantifies similarities and differences among machines. Results describe differences between process sequences, rapid traverse speeds, rapid traverse paths, machining feed speeds, machining feed paths, tool engagement time, and the temporal alignment of signals. Differences primarily originated from different control parameters and strategies as well as physical drive limitations. During machining differences occurred most frequently when axes were accelerated. Differences accumulated over prolong periods of machining and eventually became relevant from the perspective of online monitoring.
KW - knowledge transfer
KW - machine tools
KW - tool condition monitoring
UR - http://www.scopus.com/inward/record.url?scp=85172679022&partnerID=8YFLogxK
U2 - 10.1016/j.procir.2023.06.034
DO - 10.1016/j.procir.2023.06.034
M3 - Conference article
AN - SCOPUS:85172679022
VL - 118
SP - 193
EP - 198
JO - Procedia CIRP
JF - Procedia CIRP
SN - 2212-8271
Y2 - 13 July 2022 through 15 July 2022
ER -