---
res:
  bibo_abstract:
  - "<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>@eng"
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Jonathan-Markus
      foaf_name: Einwag, Jonathan-Markus
      foaf_surname: Einwag
  - foaf_Person:
      foaf_givenName: Maximilian
      foaf_name: Wiemer, Maximilian
      foaf_surname: Wiemer
  - foaf_Person:
      foaf_givenName: Sandro
      foaf_name: Wartzack, Sandro
      foaf_surname: Wartzack
  - foaf_Person:
      foaf_givenName: Stefan
      foaf_name: Goetz, Stefan
      foaf_surname: Goetz
  bibo_doi: 10.1007/s44245-026-00230-x
  bibo_issue: '1'
  bibo_volume: 5
  dct_date: 2026^xs_gYear
  dct_isPartOf:
  - http://id.crossref.org/issn/2731-6564
  dct_language: eng
  dct_publisher: Springer Science and Business Media LLC@
  dct_title: A hybrid knowledge based and data based approach for efficient clinch
    joint design@
...