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User-Centered Visual Design of Alarms in Manufacturing Dashboards: Insights on Comprehensibility and Preferences.

, , , , and . ICIS, Association for Information Systems, (2023)

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Appendix for “Unified Theory of Acceptance and Use of Technology (UTAUT) for Intelligent Process Automation“, , , and . (2023)Towards Design Principles for a Real-Time Anomaly Detection Algorithm Benchmark Suited to Industrie 4.0 Streaming Data., and . HICSS, page 1-7. ScholarSpace, (2022)Improving Machine Self-Diagnosis with an Instance-Based Selector for Real-Time Anomaly Detection Algorithms., , and . ICDSST, volume 447 of Lecture Notes in Business Information Processing, page 29-43. Springer, (2022)Assessing the Suitability of ArchiMate to Model Industry 4.0 Production Systems., , and . IIAI-AAI, page 827-832. IEEE, (2019)Towards a Student-Centered Learning Analytics Dashboard: Design, Development and Evaluation., and . AMCIS, Association for Information Systems, (2023)A Prototypical Dashboard for Knowledge-Based Expert Systems used for Real-Time Anomaly Handling in Smart Manufacturing.. HICSS, page 5582-5590. ScholarSpace, (2023)Requirements Identification for Real-Time Anomaly Detection in Industrie 4.0 Machine Groups: A Structured Literature Review., and . HICSS, page 1-10. ScholarSpace, (2021)Development and Future Research Directions of AI-Based Anomaly Detection in Smart Manufacturing: A Bibliometric Analysis, , and . 19. Internationale Tagung Wirtschaftsinformatik (WI), Würzburg, (2024)Unified Theory of Acceptance and Use of Technology (UTAUT) for Intelligent Process Automation, , , and . 44th International Conference on Information Systems (ICIS), Hyderabad, AIS, (2023)A Real-Time Semantic Anomaly Labeler Capturing Local Data Stream Features to Distinguish Anomaly Types in Production., , and . LOD (1), volume 13810 of Lecture Notes in Computer Science, page 399-413. Springer, (2022)