Optimizing Non-Isothermal Glass Molding Processes: Methodology and Comparative Analysis of Sequential and Non-Sequential Approaches

Procedia CIRP, vol. 134, pp. 354–359

Abstract

The application of machine learning (ML) for surrogate modelling in model-based optimization (MBO) of manufacturing processes offers great potential for achieving time, cost, and resource efficiency for process development. This paper explores two main optimization strategies of MBO: sequential and non-sequential optimization. We utilize a case study from non-isothermal glass molding (NGM) in which a thin glass component is formed into a 3-dimensional shape. We apply a sequential optimization approach utilizing an ML-surrogate model with Bayesian optimization. We investigate these approaches and propose a comprehensive methodology for the application of MBO, offering valuable insights for the implementation of sequential and non-sequential optimization techniques in similar manufacturing contexts. Furthermore, the results from the application on the NGM use case are compared, highlighting their effectiveness in enhancing the NGM process’s quality.

Authors 5

1. Hendrik Mende corresponding Aachen Fraunhofer Institute for Production Technology IPT

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

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

2. Lars Leyendecker Aachen Fraunhofer Institute for Production Technology IPT

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

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

3. Kashyap Upadhyay Aachen Fraunhofer Institute for Production Technology IPT

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

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

4. Dennis Grunert Aachen Fraunhofer Institute for Production Technology IPT

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

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

5. Robert Heinrich Schmitt Aachen Fraunhofer Institute for Production Technology IPT Laboratory for Machine Tools and Production Engineering WZL

   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