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Shifting Focus to Quality: An Innovative Modeling Approach Includes Processing History for Rubber Part Quality
Roman Christopher Kerschbaumer1, Georg Weinhold2, Florian Leins2
1Polymer Competence Center Leoben GmbH, Sauraugasse 1, 8700 Leoben, Austria.
Polymers
|January 25, 2025
Summary
The new average curing speed (ACS) model accurately predicts rubber part quality by including processing history. This simulation approach accounts for manufacturing variations, unlike traditional methods, ensuring reliable quality predictions.
Area of Science:
- Materials Science
- Polymer Engineering
- Computational Modeling
Background:
- Traditional rubber part quality simulations often neglect processing history, leading to inaccurate predictions.
- Existing models rely on temperature-based approaches, failing to capture the impact of manufacturing variations on final part properties.
- Correlation between simulated cure degree and actual part quality requires post-simulation analysis or separate numerical tools.
Purpose of the Study:
- To introduce an innovative modeling approach, the average curing speed (ACS) model, for simulating rubber part quality.
- To integrate processing history directly into the filling and curing simulation for more accurate quality prediction.
- To demonstrate the ACS model's ability to correlate simulation with real-world part quality through a single calibration step.
Main Methods:
- Developed the average curing speed (ACS) model, focusing on degree of cure and average curing speed.
- Manufactured rubber parts using compression molding across a range of mold temperatures (140-170 °C) and cure degrees (24-99%).
- Analyzed the permanent deformation, specifically compression set (CS), of manufactured parts to validate the model.
Main Results:
- The ACS model successfully incorporates processing history into simulations, unlike conventional methods.
- Experimental results showed significant variations in compression set (CS) for the same degree of cure at different mold temperatures.
- The ACS model demonstrated its capability to accurately predict part quality, aligning simulated results with manufactured part quality.
Conclusions:
- The ACS model overcomes the limitations of traditional approaches by accounting for processing history.
- This simulation routine provides a powerful tool for understanding and optimizing local variations in rubber part quality.
- The ACS model, implemented in SIGMASOFT® v6.0, offers significant potential for improving rubber part design and manufacturing.
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