Next generation of composite manufacturing using digitalization
To optimize the production of composite materials, FHNW researchers have succeeded in enabling cyber-physical systems to monitor and transfer real production conditions to virtual environments.
Background
In Switzerland around 150 companies are working in the field of composite materials. They manufacture composite structures for high performance applications. In contrast to conventional materials like metals, the mechanical performance of composite parts is highly dependent on the manufacturing process itself and “as‑built” performance can differ substantially from the initial design models. By adjusting the digital model to reflect the real variability seen in initial production trials, both the design and process could be optimized to maximize component performance and production economics.
Goals
The project develops a breakthrough system of connected software and hardware to enable the generation of a “digital twin” for thermoset composite manufacturing. A coupled cyber physical system will be developed to capture data from the shop floor during manufacture and enable the creation of the digital twin model. This manufacturing will combine innovations in the following three technology areas: (1) online process monitoring (2) a holistic standards based approach to store manufacturing related data and (3) software to interpret this data to enable simulation of the “As-built” condition.
Results
Within the project, it has been possible to enable cyber physical systems for monitoring and transferring real production states to virtual environments. Machine vision methods and machine learning algorithms have been used to accompany the production of high-tech composite materials. The use of numerical computational methods with the data of real component conditions is thus enabled in the virtual environment and could be implemented within the project for three use cases.
Project-Information | |
Client | |
Execution | FHNW Institut of Polymer Engineering |
Dauer | 2 years |
Förderung | Innosuisse |
Projektteam | Oliver Döbrich, Ayoh Anderegg, Christian Brauner |