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Artif. Intell."],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Ensuring consistent product quality in modern manufacturing is crucial, particularly in safety-critical applications. Conventional quality control approaches rely on manually defined features and lack adaptability to the complexity and variability inherent in production data. Conversely, data-driven methods, such as machine learning, demonstrate high detection performance but typically function as black-box models, thereby limiting their acceptance in industrial environments. This paper introduces a methodology for industrial fault detection in the domain of crimping, a safety-critical joining technique, which is both data-driven and transparent. The approach integrates a supervised machine learning model for multi-class fault classification, Shapley Additive Explanations for post-hoc interpretability and a domain-specific visualization technique that maps model explanations to interpretable features. The model explanations are assessed with a quantitative perturbation analysis and the visualization technique is evaluated qualitatively by domain experts. The approach achieves a fault detection accuracy of 95.9 %, and both quantitative selectivity analysis and qualitative expert evaluations confirmed the relevance of the generated explanations. This case study contributes to data-driven and interpretable quality control systems in manufacturing.<\/jats:p>","DOI":"10.1007\/s44244-026-00028-6","type":"journal-article","created":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T16:56:48Z","timestamp":1774976208000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Transparent machine learning for crimp force monitoring using phase-based SHAP explanations"],"prefix":"10.1007","volume":"4","author":[{"given":"Bernd","family":"Hofmann","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patrick","family":"Br\u00fcndl","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huong Giang","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J\u00f6rg","family":"Franke","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,3,31]]},"reference":[{"key":"28_CR1","unstructured":"International Electrotechnical Commission: Solderless Connections\u2013Part 2: Crimped Connections\u2013General Requirements, Test Methods and Practical Guidance (2021)"},{"key":"28_CR2","doi-asserted-by":"publisher","first-page":"2306820","DOI":"10.1080\/21693277.2024.2306820","volume":"12","author":"P Br\u00fcndl","year":"2024","unstructured":"Br\u00fcndl P, Stoidner M, Bredthauer J, Nguyen HG, Baechler A, Franke J (2024) Unlocking the potential of digitalization and automation: a qualitative and quantitative study of the control cabinet manufacturing industry. 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