Polymer processing with thermosets is the key to high-performance parts regarding mechanical strength and durability. However, the material causes many challenges in production. In a customer-centric approach, the new sensXPERT solution provides a state-of-the-art solution to tackle lacking transparency and high scrap rates. sensXPERT delivers a unique solution for processors in the polymer and polymer based composite field while combining sensors, material science and machine learning. Read about the importance of the partnership with AIRBUS to provide this solution.
The automotive and aviation industry may use different processes, but they face the same problems in their production: They strive to achieve higher efficiency in form of faster cycle times, reduced scrap production and a dynamic process control.
Thermosets and thermosetting composites are used to produce high-performance parts regarding mechanical strength. However, tailoring the chemistry to the application has led to a huge variety of different resin families and special formulations - whose behavior isn’t fully understood - the material causes many challenges in production. For many years and together with our customers, we have observed and analyzed the hurdles that hamper the industry to achieve its full potential.
Producers of polymer components lack vital transparency in their processes. In the most critical process steps of curing the parts and components, the process does not provide any information if the product will be a good or bad part or if there is wasted efficiency.
We realized that there is a clear need for more transparency and traceability of material data in order to control the production process based on the optimal curing of the material.
AIRBUS, a leading aircraft manufacturer selected NETZSCH Analyzing &Testing to provide an intelligent sensor solution based on its dielectric measurement technology. With a formed start-up team acting under the name sensXPERT, NETZSCH offers a new way of polymer and polymer based composite manufacturing by combining innovative sensors with advanced analytics and machine learning.
During the manufacturing process, sensors installed in the mold measure crucial material properties like degree-of-cure and glass-transition temperature in real time in order to increase the production efficiency. Material science paired with data from the real process environment bring artificial intelligence to the manufacturing site while creating dynamic processes based on historical and new data with the use of machine learning. Data of different batches, deviations due to transport and storing, climate influences, impurities – all will be taken into account to ensure are liable and robust component processing.
The all-in-one solution provides a full overview of the entire production displayed in customizable dashboards andallows the qualification of components during the processing. Additionally, notifications of the current state of production are available whenever and wherever one may want to receive them.
“We are pleased to have been selected by Airbus to develop the sensXPERT solution in a customer-centric way. The long-standing collaboration with Airbus has given the project an incredible boost. During the last months, we have made rapid strides to release the product in 2021.”
As the collaboration is ongoing, AIRBUS R&T Composite team is going to use the sensXPERT solution with different materials in different process scenarios. The first validation trials have shown that sensXPERT is capable of detecting crucial parameters like degree-of-cure and glass-transition temperature with very small discrepancies compared to high sensitive laboratory measurements based on existing standards using a differential scanning calorimeter as reference.
SensXPERT transforms manufacturing processes to higher standards by allowing our customers to:
· Reduce scrap and achieve operational excellence
· Increase throughput with real-time process optimization
· Reach highest equipment effectiveness
· Transparency and traceability of production displayed in customizable dashboards
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