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This study introduces a Bayesian optimization method to enhance automotive seal production by minimizing defects caused by process and material uncertainties. The model-based approach achieves a 50% tighter dimensional tolerance, improving product quality without extra costs.

Keywords:
Bayesian optimizationExtrusion processReduced order modelRobustness

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Area of Science:

  • Manufacturing Engineering
  • Materials Science
  • Optimization Theory

Background:

  • Automotive seal production faces challenges with high throughput, quality constraints, and process uncertainties.
  • Variability in extrusion processes and raw materials significantly impacts seal quality and leads to nonconformities.
  • Existing deterministic methods struggle to effectively manage these inherent uncertainties.

Purpose of the Study:

  • To propose a model-based optimization method for automotive seal extrusion that robustly handles process and material uncertainties.
  • To minimize nonconformities and improve product quality in high-throughput manufacturing environments.
  • To develop a cost-effective solution for enhancing dimensional tolerance in automotive seals.

Main Methods:

  • Utilized Bayesian optimization for robust process parameter selection.
  • Employed a reduced-order model to overcome the computational cost of detailed simulations.
  • Integrated consideration of process variability and raw material uncertainty into the optimization framework.

Main Results:

  • The proposed Bayesian optimization method effectively minimizes the impact of process uncertainties in a virtual environment.
  • Achieved a 50% tighter dimensional tolerance compared to deterministic optimization algorithms.
  • Demonstrated significant product quality improvement without incurring additional manufacturing costs.

Conclusions:

  • Model-based Bayesian optimization offers a robust and cost-effective solution for improving automotive seal extrusion.
  • The method successfully addresses inherent process and material uncertainties, leading to enhanced product quality.
  • This approach provides a significant advancement in achieving tighter dimensional tolerances and reducing nonconformities in manufacturing.