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Download statistics - Document (COUNTER):
Brüning, J.; Denkena, B.; Dittrich, M.-A.; Hocke, T.: Machine Learning Approach for Optimization of Automated Fiber Placement Processes. In: Procedia CIRP 66 (2017), S. 74-78. DOI: https://doi.org/10.1016/j.procir.2017.03.295
Repository version
Selected time period:
Sum total of downloads: 806
| Abstract: | |
Automated Fiber Placement (AFP) processes are commonly deployed in manufacturing of lightweight structures made of carbon fibre reinforced polymer. In general, AFP is connected to individual manufacturing knowledge during process planning and time consuming manual quality inspections. In both cases, automatic solutions provide a high economic potential. Therefore, a machine learning approach for planning, optimizing and inspection of AFP processes is presented. Process data from planning, CNC and online process monitoring is aggregated for the documentation of the part specific manufacturing history and the automated generation of manufacturing knowledge. Within this approach a complete automation of data capturing, data storing, modeling and optimizing is achieved. | |
| License of this version: | CC BY-NC-ND 4.0 Unported |
| Document Type: | Article |
| Publishing status: | publishedVersion |
| Issue Date: | 2017 |
| Appears in Collections: | Fakultät für Maschinenbau |
distribution of downloads over the selected time period:
downloads by country:
| pos. | country | downloads | ||
|---|---|---|---|---|
| total | perc. | |||
| 1 |  |
Germany | 351 | 43.55% |
| 2 |  |
United States | 112 | 13.90% |
| 3 |  |
China | 41 | 5.09% |
| 4 |  |
Russian Federation | 29 | 3.60% |
| 5 |  |
United Kingdom | 24 | 2.98% |
| 6 |  |
Turkey | 16 | 1.99% |
| 7 |  |
Korea, Republic of | 16 | 1.99% |
| 8 |  |
India | 16 | 1.99% |
| 9 |  |
Iran, Islamic Republic of | 14 | 1.74% |
| 10 |  |
France | 13 | 1.61% |
| other countries | 174 | 21.59% | ||
Further download figures and rankings:
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