A

Multi-Objective Lookahead Bayesian Optimization for Process Parameter Optimization in Non-Isothermal Glass Molding

Procedia CIRP, vol. 134, pp. 366–371

Abstract

The optimization of non-isothermal glass molding (NGM) processes is crucial for attaining precise shape accuracy of optical components. Identifying optimal parameters poses a challenge due to unknown functional relationships and high-dimensional design and target spaces. Traditional design of experiments (DoE) approaches are sample inefficient in this regard. This paper presents a multi-objective lookahead Bayesian optimization framework applied to a use case from NGM, in which a glass gob is formed into a light optic. The approach leverages a multi-target Gaussian Process-based surrogate model. Through novel acquisition functions, the framework adeptly balances exploration and exploitation, resulting in a significant reduction of samples necessary. Improved peak-to-valley values for the glass optics demonstrate the improvement of the product quality with regard to the application of the approach. The developed framework offers a flexible, efficient approach, contributing to industrial process optimization.

Authors 5

  1. Fraunhofer Institute for Production Technology IPT

    Affiliation as printed

    Fraunhofer Institute for Production Technology IPT, Steinbachstr. 17, Aachen 52074, Germany

  2. Fraunhofer Institute for Production Technology IPT

    Affiliation as printed

    Fraunhofer Institute for Production Technology IPT, Steinbachstr. 17, Aachen 52074, Germany

  3. Fraunhofer Institute for Production Technology IPT

    Affiliation as printed

    Fraunhofer Institute for Production Technology IPT, Steinbachstr. 17, Aachen 52074, Germany

  4. Fraunhofer Institute for Production Technology IPT

    Affiliation as printed

    Fraunhofer Institute for Production Technology IPT, Steinbachstr. 17, Aachen 52074, Germany

  5. Fraunhofer Institute for Production Technology IPT · RWTH Aachen University

    Affiliation as printed

    Fraunhofer Institute for Production Technology IPT, Steinbachstr. 17, Aachen 52074, Germany

    Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen University, Campus-Boulevard 30, Aachen 52074, Germany

Cited by 0 stored of 0

No patents citing this paper on Lens.org (checked 2026-10-06).

References 17

17 results