---
_id: '65620'
abstract:
- lang: eng
  text: "<jats:title>Abstract</jats:title>\r\n                  <jats:p>The design
    of clinch joints is a cost- and time-intensive iterative process due to the complex
    relationships between tool and process parameters and the resulting joint properties.
    To address this, this contribution proposes a novel hybrid workflow that combines
    knowledge- and data-based approaches. Relationships are categorized based on their
    knowledge quality and the need for a quantitative prediction. Well-established,
    generalizable relationships are formalized in an ontology as design guidelines
    (no quantification required) or SWRL rules (quantification required) to model
    expert knowledge. In contrast, hard-to-formalize or not-fully-understood relationships
    are treated with regression models for continuous or classification models for
    binary criteria. These approaches are combined in a generic user interface (GUI),
    where the ontology can be accessed using predefined SPARQL queries to select and
    adapt parameters using expert knowledge. These parameters are then used as input
    for the metamodels. The developed workflow is evaluated on two exemplary joining
    tasks to illustrate, how designers can retrieve similar prior joints, adapt parameters
    using the encoded design rules and predict resulting joint properties under varying
    process conditions. In summary, the combination of ontology and metamodels facilitates
    the transition of trial and error into an efficient, documentable design process.</jats:p>"
article_number: '56'
author:
- first_name: Jonathan-Markus
  full_name: Einwag, Jonathan-Markus
  last_name: Einwag
- first_name: Maximilian
  full_name: Wiemer, Maximilian
  last_name: Wiemer
- first_name: Sandro
  full_name: Wartzack, Sandro
  last_name: Wartzack
- first_name: Stefan
  full_name: Goetz, Stefan
  last_name: Goetz
citation:
  ama: Einwag J-M, Wiemer M, Wartzack S, Goetz S. A hybrid knowledge based and data
    based approach for efficient clinch joint design. <i>Discover Mechanical Engineering</i>.
    2026;5(1). doi:<a href="https://doi.org/10.1007/s44245-026-00230-x">10.1007/s44245-026-00230-x</a>
  apa: Einwag, J.-M., Wiemer, M., Wartzack, S., &#38; Goetz, S. (2026). A hybrid knowledge
    based and data based approach for efficient clinch joint design. <i>Discover Mechanical
    Engineering</i>, <i>5</i>(1), Article 56. <a href="https://doi.org/10.1007/s44245-026-00230-x">https://doi.org/10.1007/s44245-026-00230-x</a>
  bibtex: '@article{Einwag_Wiemer_Wartzack_Goetz_2026, title={A hybrid knowledge based
    and data based approach for efficient clinch joint design}, volume={5}, DOI={<a
    href="https://doi.org/10.1007/s44245-026-00230-x">10.1007/s44245-026-00230-x</a>},
    number={156}, journal={Discover Mechanical Engineering}, publisher={Springer Science
    and Business Media LLC}, author={Einwag, Jonathan-Markus and Wiemer, Maximilian
    and Wartzack, Sandro and Goetz, Stefan}, year={2026} }'
  chicago: Einwag, Jonathan-Markus, Maximilian Wiemer, Sandro Wartzack, and Stefan
    Goetz. “A Hybrid Knowledge Based and Data Based Approach for Efficient Clinch
    Joint Design.” <i>Discover Mechanical Engineering</i> 5, no. 1 (2026). <a href="https://doi.org/10.1007/s44245-026-00230-x">https://doi.org/10.1007/s44245-026-00230-x</a>.
  ieee: 'J.-M. Einwag, M. Wiemer, S. Wartzack, and S. Goetz, “A hybrid knowledge based
    and data based approach for efficient clinch joint design,” <i>Discover Mechanical
    Engineering</i>, vol. 5, no. 1, Art. no. 56, 2026, doi: <a href="https://doi.org/10.1007/s44245-026-00230-x">10.1007/s44245-026-00230-x</a>.'
  mla: Einwag, Jonathan-Markus, et al. “A Hybrid Knowledge Based and Data Based Approach
    for Efficient Clinch Joint Design.” <i>Discover Mechanical Engineering</i>, vol.
    5, no. 1, 56, Springer Science and Business Media LLC, 2026, doi:<a href="https://doi.org/10.1007/s44245-026-00230-x">10.1007/s44245-026-00230-x</a>.
  short: J.-M. Einwag, M. Wiemer, S. Wartzack, S. Goetz, Discover Mechanical Engineering
    5 (2026).
date_created: 2026-05-13T11:46:44Z
date_updated: 2026-05-13T11:50:48Z
doi: 10.1007/s44245-026-00230-x
intvolume: '         5'
issue: '1'
language:
- iso: eng
project:
- _id: '130'
  name: 'TRR 285:  Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen
    Prozessketten'
- _id: '132'
  name: TRR 285 - Project Area B
- _id: '144'
  name: TRR 285 - Subproject B05
publication: Discover Mechanical Engineering
publication_identifier:
  issn:
  - 2731-6564
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: A hybrid knowledge based and data based approach for efficient clinch joint
  design
type: journal_article
user_id: '107109'
volume: 5
year: '2026'
...