Details
| Original language | English |
|---|---|
| Pages (from-to) | 1-6 |
| Number of pages | 6 |
| Journal | Procedia CIRP |
| Volume | 100 |
| Early online date | 2 Jun 2021 |
| Publication status | Published - 2021 |
| Event | 31st CIRP Design Conference 2021, CIRP Design 2021 - Enschede, Netherlands Duration: 19 May 2021 → 21 May 2021 |
Abstract
The bond strength between a thermoformed fibre reinforced thermoplastic sheet and an injected polymer is the limiting factor for the structural integrity of overmoulded thermoplastic composites. In this contribution, a simulation based digital twin of the thermoforming process is presented. From numerical parametric studies a reduced order model based on Proper Orthogonal Decomposition (POD) is developed. The combination with machine learning methods enables the real-time computation of arbitrary physical reliable temperature fields with sufficient accuracy to be used for design purposes and as inline quality gates.
Keywords
- Digital Twin, Finite Element Method, Reduced Order Modelling, Thermoforming, Thermoplastic Composites
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Engineering(all)
- Industrial and Manufacturing Engineering
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In: Procedia CIRP, Vol. 100, 2021, p. 1-6.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Simulation-based digital twin for the manufacturing of thermoplastic composites
AU - Hürkamp, André
AU - Lorenz, Ralf
AU - Ossowski, Tim
AU - Behrens, Bernd Arno
AU - Dröder, Klaus
N1 - Funding Information: This research and results published are based on the research program Mobilise funded by the Ministry of Science and Culture of Lower Saxony and the Volkswagen Foundation and the IGF-Project “Integrated process simulation of thermoforming and injection moulding“ of the European Research Association for Sheet Metal Working (EFB e.V.) funded by the Federal Ministry of Economics and Energy (BMWi) under the funding number 20524N of the German Federation of Industrial Research Associations (AiF). The authors gratefully acknowledge this financial support.
PY - 2021
Y1 - 2021
N2 - The bond strength between a thermoformed fibre reinforced thermoplastic sheet and an injected polymer is the limiting factor for the structural integrity of overmoulded thermoplastic composites. In this contribution, a simulation based digital twin of the thermoforming process is presented. From numerical parametric studies a reduced order model based on Proper Orthogonal Decomposition (POD) is developed. The combination with machine learning methods enables the real-time computation of arbitrary physical reliable temperature fields with sufficient accuracy to be used for design purposes and as inline quality gates.
AB - The bond strength between a thermoformed fibre reinforced thermoplastic sheet and an injected polymer is the limiting factor for the structural integrity of overmoulded thermoplastic composites. In this contribution, a simulation based digital twin of the thermoforming process is presented. From numerical parametric studies a reduced order model based on Proper Orthogonal Decomposition (POD) is developed. The combination with machine learning methods enables the real-time computation of arbitrary physical reliable temperature fields with sufficient accuracy to be used for design purposes and as inline quality gates.
KW - Digital Twin
KW - Finite Element Method
KW - Reduced Order Modelling
KW - Thermoforming
KW - Thermoplastic Composites
UR - http://www.scopus.com/inward/record.url?scp=85107892250&partnerID=8YFLogxK
U2 - 10.1016/j.procir.2021.05.001
DO - 10.1016/j.procir.2021.05.001
M3 - Conference article
AN - SCOPUS:85107892250
VL - 100
SP - 1
EP - 6
JO - Procedia CIRP
JF - Procedia CIRP
SN - 2212-8271
T2 - 31st CIRP Design Conference 2021, CIRP Design 2021
Y2 - 19 May 2021 through 21 May 2021
ER -