Details
| Original language | English |
|---|---|
| Title of host publication | 6th CIRP Global Web Conference, CIRPe 2018 |
| Subtitle of host publication | Envisaging the Future Manufacturing, Design, Technologies and Systems in Innovation Era |
| Editors | Alessandro Simeone, Paolo C. Priarone |
| Publisher | Elsevier Science B.V. |
| Pages | 313-317 |
| Number of pages | 5 |
| ISBN (electronic) | 9781510875692 |
| Publication status | Published - 24 Nov 2018 |
| Event | 6th CIRP Global Web Conference, CIRPe 2018 - Duration: 23 Oct 2018 → 25 Oct 2018 |
Publication series
| Name | Procedia CIRP |
|---|---|
| Volume | 78 |
| ISSN (Print) | 2212-8271 |
Abstract
Despite recent advances in automation technology, geometrically complex workpieces are still often finished manually. An example for this is the post-processing of dental prostheses, which display exceptionally high surface requirements. Aiming for an improved quality assurance, this article presents a methodology for an adaptive tool path planning for polishing of geometrically complex workpieces. For this purpose, the initial roughness of the workpiece is determined using a machine-integrated measuring system. Next, suitable process parameters are selected based on machine knowledge and the adapted NC code of the polishing process is generated and simulated. The results of the simulation and the actual polishing process are compared afterwards and transformed into process knowledge. Thus, the adaption of the process parameters and the quality of the simulation are continuously improved. The article highlights the implementation of the methodology with special emphasis on the selection of the process parameters.
Keywords
- Computer aided manufacturing (CAM), Machine learning, Polishing
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Engineering(all)
- Industrial and Manufacturing Engineering
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6th CIRP Global Web Conference, CIRPe 2018: Envisaging the Future Manufacturing, Design, Technologies and Systems in Innovation Era. ed. / Alessandro Simeone; Paolo C. Priarone. Elsevier Science B.V., 2018. p. 313-317 (Procedia CIRP; Vol. 78).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Technological CAD/CAM chain for automated polishing of geometrically complex workpieces
AU - Denkena, Berend
AU - Dittrich, Marc André
AU - Nguyen, Hai Nam
N1 - Funding information: These investigations were funded by the German Federal Ministry of Economics and Energy (ZF4078502) and carried out in cooperation with the companies Akcurate GmbH and EVE Ernst Vetter GmbH. The authors thank our cooperation partners for their support in the project.
PY - 2018/11/24
Y1 - 2018/11/24
N2 - Despite recent advances in automation technology, geometrically complex workpieces are still often finished manually. An example for this is the post-processing of dental prostheses, which display exceptionally high surface requirements. Aiming for an improved quality assurance, this article presents a methodology for an adaptive tool path planning for polishing of geometrically complex workpieces. For this purpose, the initial roughness of the workpiece is determined using a machine-integrated measuring system. Next, suitable process parameters are selected based on machine knowledge and the adapted NC code of the polishing process is generated and simulated. The results of the simulation and the actual polishing process are compared afterwards and transformed into process knowledge. Thus, the adaption of the process parameters and the quality of the simulation are continuously improved. The article highlights the implementation of the methodology with special emphasis on the selection of the process parameters.
AB - Despite recent advances in automation technology, geometrically complex workpieces are still often finished manually. An example for this is the post-processing of dental prostheses, which display exceptionally high surface requirements. Aiming for an improved quality assurance, this article presents a methodology for an adaptive tool path planning for polishing of geometrically complex workpieces. For this purpose, the initial roughness of the workpiece is determined using a machine-integrated measuring system. Next, suitable process parameters are selected based on machine knowledge and the adapted NC code of the polishing process is generated and simulated. The results of the simulation and the actual polishing process are compared afterwards and transformed into process knowledge. Thus, the adaption of the process parameters and the quality of the simulation are continuously improved. The article highlights the implementation of the methodology with special emphasis on the selection of the process parameters.
KW - Computer aided manufacturing (CAM)
KW - Machine learning
KW - Polishing
UR - http://www.scopus.com/inward/record.url?scp=85059911465&partnerID=8YFLogxK
U2 - 10.1016/j.procir.2018.09.049
DO - 10.1016/j.procir.2018.09.049
M3 - Conference contribution
AN - SCOPUS:85059911465
T3 - Procedia CIRP
SP - 313
EP - 317
BT - 6th CIRP Global Web Conference, CIRPe 2018
A2 - Simeone, Alessandro
A2 - Priarone, Paolo C.
PB - Elsevier Science B.V.
T2 - 6th CIRP Global Web Conference, CIRPe 2018
Y2 - 23 October 2018 through 25 October 2018
ER -