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dc.contributor.authorRehse, Jana-Rebecca
dc.contributor.authorMehdiyev, Nijat
dc.contributor.authorFettke, Peter
dc.date2019-06-01
dc.date.accessioned2021-04-23T09:25:51Z
dc.date.available2021-04-23T09:25:51Z
dc.date.issued2019
dc.identifier.issn1610-1987
dc.identifier.urihttp://dx.doi.org/10.1007/s13218-019-00586-1
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/36236
dc.description.abstractWith the advent of digitization on the shopfloor and the developments of Industry 4.0, companies are faced with opportunities and challenges alike. This can be illustrated by the example of AI-based process predictions, which can be valuable for real-time process management in a smart factory. However, to constructively collaborate with such a prediction, users need to establish confidence in its decisions. Explainable artificial intelligence (XAI) has emerged as a new research area to enable humans to understand, trust, and manage the AI they work with. In this contribution, we illustrate the opportunities and challenges of process predictions and XAI for Industry 4.0 with the DFKI-Smart-Lego-Factory. This fully automated factory prototype built out of LEGO $$^\circledR$$ ® bricks demonstrates the potentials of Industry 4.0 in an innovative, yet easily accessible way. It includes a showcase that predicts likely process outcomes and uses state-of-the-art XAI techniques to explain them to its workers and visitors.de
dc.publisherSpringer
dc.relation.ispartofKI - Künstliche Intelligenz: Vol. 33, No. 2
dc.relation.ispartofseriesKI - Künstliche Intelligenz
dc.subjectExplainable artificial Intelligence
dc.subjectIndustry 4.0
dc.subjectProcess prediction
dc.subjectSmart factories
dc.titleTowards Explainable Process Predictions for Industry 4.0 in the DFKI-Smart-Lego-Factoryde
dc.typeText/Journal Article
mci.reference.pages181-187
dc.identifier.doi10.1007/s13218-019-00586-1


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