Assessing the Suitability of ArchiMate to Model Industry 4.0 Production Systems. - Dennis Horstkemper; Philip Stahmann; Bernd Hellingrath (IIAI-AAI, 2019)

Requirements Identification for Real-Time Anomaly Detection in Industrie 4.0 Machine Groups: A Structured Literature Review. - Philip Stahmann; Bodo Rieger (HICSS, 2021)

Digital Twins for Real-time Data Analysis in Industrie 4.0: Pathways to Maturity. - Philip Stahmann; Arne Krüger; Bodo Rieger (IN4PL, 2021)

Improving Machine Self-Diagnosis with an Instance-Based Selector for Real-Time Anomaly Detection Algorithms. - Philip Stahmann; Jon Oodes; Bodo Rieger (ICDSST, 2022)

Towards Design Principles for a Real-Time Anomaly Detection Algorithm Benchmark Suited to Industrie 4.0 Streaming Data. - Philip Stahmann; Bodo Rieger (HICSS, 2022)

A Real-Time Semantic Anomaly Labeler Capturing Local Data Stream Features to Distinguish Anomaly Types in Production. - Philip Stahmann; Maximilian Nebel; Bodo Rieger (LOD (1), 2022)

A Benchmark for Real-Time Anomaly Detection Algorithms Applied in Industry 4.0. - Philip Stahmann; Bodo Rieger (LOD (1), 2022)

Towards a Student-Centered Learning Analytics Dashboard: Design, Development and Evaluation. - Alena Rodda; Philip Stahmann (AMCIS, 2023)

The effect of Advanced Analytics Real-Time Dashboards on Cognitive absorption and Task Load of Human End Users. - Philip Stahmann; Alena Rodda; Christian Janiesch (ECIS, 2023)

A Prototypical Dashboard for Knowledge-Based Expert Systems used for Real-Time Anomaly Handling in Smart Manufacturing. - Philip Stahmann (HICSS, 2023)

Unified Theory of Acceptance and Use of Technology (UTAUT) for Intelligent Process Automation. - Alexander Mayr; Philip Stahmann; Maximilian Nebel; Christian Janiesch (ICIS, 2023)

User-Centered Visual Design of Alarms in Manufacturing Dashboards: Insights on Comprehensibility and Preferences. - Philip Stahmann; Laura Sophie Gravemeier; Anke Dittmer; Christian Janiesch; Oliver Thomas 001 (ICIS, 2023)

Development and Future Research Directions of AI-Based Anomaly Detection in Smart Manufacturing: A Bibliometric Analysis. - Maximilian Nebel; Philip Stahmann; Christian Janiesch (Wirtschaftsinformatik, 2024)

Still doing it yourself? Investigating determinants for the adoption of intelligent process automation. - Alexander Mayr; Philip Stahmann; Maximilian Nebel; Christian Janiesch (Electron. Mark., 2024)

AI-based real-time anomaly detection in industrial engineering: A structured literature review, taxonomy, and research agenda. - Philip Stahmann; Maximilian Nebel; Christian Janiesch (Comput. Ind. Eng., 2025)