---
_id: '29803'
abstract:
- lang: eng
  text: "Ultrasonic wire bonding is a solid-state joining process used to form electrical
    interconnections in micro and\r\npower electronics and batteries. A high frequency
    oscillation causes a metallurgical bond deformation in\r\nthe contact area. Due
    to the numerous physical influencing factors, it is very difficult to accurately
    capture\r\nthis process in a model. Therefore, our goal is to determine a suitable
    feed-forward control strategy for the\r\nbonding process even without detailed
    model knowledge. We propose the use of batch constrained Bayesian\r\noptimization
    for the control design. Hence, Bayesian optimization is precisely adapted to the
    application of\r\nbonding: the constraint is used to check one quality feature
    of the process and the use of batches leads to\r\nmore efficient experiments.
    Our approach is suitable to determine a feed-forward control for the bonding\r\nprocess
    that provides very high quality bonds without using a physical model. We also
    show that the quality\r\nof the Bayesian optimization based control outperforms
    random search as well as manual search by a user.\r\nUsing a simple prior knowledge
    model derived from data further improves the quality of the connection.\r\nThe
    Bayesian optimization approach offers the possibility to perform a sensitivity
    analysis of the control\r\nparameters, which allows to evaluate the influence
    of each control parameter on the bond quality. In summary,\r\nBayesian optimization
    applied to the bonding process provides an excellent opportunity to develop a
    feedforward\r\ncontrol without full modeling of the underlying physical processes."
author:
- first_name: Michael
  full_name: Hesse, Michael
  id: '29222'
  last_name: Hesse
- first_name: Matthias
  full_name: Hunstig, Matthias
  last_name: Hunstig
- first_name: Julia
  full_name: Timmermann, Julia
  id: '15402'
  last_name: Timmermann
- first_name: Ansgar
  full_name: Trächtler, Ansgar
  id: '552'
  last_name: Trächtler
citation:
  ama: 'Hesse M, Hunstig M, Timmermann J, Trächtler A. Batch Constrained Bayesian
    Optimization for UltrasonicWire Bonding Feed-forward Control Design. In: <i>Proceedings
    of the 11th International Conference on Pattern Recognition Applications and Methods
    (ICPRAM)</i>. ; 2022:383-394.'
  apa: Hesse, M., Hunstig, M., Timmermann, J., &#38; Trächtler, A. (2022). Batch Constrained
    Bayesian Optimization for UltrasonicWire Bonding Feed-forward Control Design.
    <i>Proceedings of the 11th International Conference on Pattern Recognition Applications
    and Methods (ICPRAM)</i>, 383–394.
  bibtex: '@inproceedings{Hesse_Hunstig_Timmermann_Trächtler_2022, title={Batch Constrained
    Bayesian Optimization for UltrasonicWire Bonding Feed-forward Control Design},
    booktitle={Proceedings of the 11th International Conference on Pattern Recognition
    Applications and Methods (ICPRAM)}, author={Hesse, Michael and Hunstig, Matthias
    and Timmermann, Julia and Trächtler, Ansgar}, year={2022}, pages={383–394} }'
  chicago: Hesse, Michael, Matthias Hunstig, Julia Timmermann, and Ansgar Trächtler.
    “Batch Constrained Bayesian Optimization for UltrasonicWire Bonding Feed-Forward
    Control Design.” In <i>Proceedings of the 11th International Conference on Pattern
    Recognition Applications and Methods (ICPRAM)</i>, 383–94, 2022.
  ieee: M. Hesse, M. Hunstig, J. Timmermann, and A. Trächtler, “Batch Constrained
    Bayesian Optimization for UltrasonicWire Bonding Feed-forward Control Design,”
    in <i>Proceedings of the 11th International Conference on Pattern Recognition
    Applications and Methods (ICPRAM)</i>, Online, 2022, pp. 383–394.
  mla: Hesse, Michael, et al. “Batch Constrained Bayesian Optimization for UltrasonicWire
    Bonding Feed-Forward Control Design.” <i>Proceedings of the 11th International
    Conference on Pattern Recognition Applications and Methods (ICPRAM)</i>, 2022,
    pp. 383–94.
  short: 'M. Hesse, M. Hunstig, J. Timmermann, A. Trächtler, in: Proceedings of the
    11th International Conference on Pattern Recognition Applications and Methods
    (ICPRAM), 2022, pp. 383–394.'
conference:
  end_date: 2022-02-05
  location: Online
  name: 11th International Conference on Pattern Recognition Applications and Methods
  start_date: 2022-02-03
date_created: 2022-02-09T12:50:25Z
date_updated: 2024-11-13T08:44:17Z
department:
- _id: '153'
- _id: '880'
keyword:
- Bayesian optimization
- Wire bonding
- Feed-forward control
- model-free design
language:
- iso: eng
page: 383-394
publication: Proceedings of the 11th International Conference on Pattern Recognition
  Applications and Methods (ICPRAM)
publication_identifier:
  isbn:
  - 978-989-758-549-4
quality_controlled: '1'
status: public
title: Batch Constrained Bayesian Optimization for UltrasonicWire Bonding Feed-forward
  Control Design
type: conference
user_id: '82875'
year: '2022'
...