Explainability of Quality Issues in Manufacturing: a Semantic Based Approach
Résumé
This paper presents an approach using stream reasoning for detecting manufacturing quality losses. To semantically detect quality issues situations, an ontology-based context for manufacturing is introduced. Moreover, as heterogeneous data streams have to be integrated, a combination of existing models using stream processing and offline reasoning can be used. This combination allows continuous processing of data and the use of expert knowledge to detect anomalies and provide explanations to operators and stakeholders. An illustrative case study about quality assurance succeeded in detecting anomalies and proposing an explanation.
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