activity
20242026
most citedTowards Precision in Bolted Joint Design: A Preliminary Machine Learning-Based Parameter Prediction

5 citations · 6 across the 4 of their papers we have counts for

collaborators

5 papers

eess.SY2026

Unified Embodiment Description for functional evaluation of used components in circular manufacturing systems

Jonas Hemmerich, Dominik Koch, Victor Mas +5

Circular manufacturing systems require functional evaluation of used components based on their physical state. Existing approaches describe this state from separate perspectives, s…

cs.AI2026

Uncertainty Aware Functional Behavior Prediction and Material Fatigue Assessment for Circular Factory

Nehal Afifi, Mehdi Khabou, Victor Mas +5

Returned products in circular factories re-enter production with heterogeneous degradation states, usage histories, and remaining capability. Reuse cannot be decided from the curre…

cs.LG2026

Anomaly Detection for Electro-Hydrostatic Actuators using LSTM Autoencoder

Nehal Afifi, Abdelmonem Elhendawi, Felix Leitenberger +2

Electro-Hydrostatic Actuators (EHAs) are widely used in aerospace and industrial systems, where timely detection of sensor anomalies is essential to ensure safe and reliable operat…

cs.SE2025★ 1 cited

Data-Driven Methods and AI in Engineering Design: A Systematic Literature Review Focusing on Challenges and Opportunities

Nehal Afifi, Christoph Wittig, Lukas Paehler +8

The increasing availability of data and advancements in computational intelligence have accelerated the adoption of data-driven methods (DDMs) in product development. However, thei…

cs.LG2024★ 5 cited

Towards Precision in Bolted Joint Design: A Preliminary Machine Learning-Based Parameter Prediction

Ines Boujnah, Nehal Afifi, Andreas Wettstein +1

Bolted joints are critical in engineering for maintaining structural integrity and reliability. Accurate prediction of parameters influencing their function and behavior is essenti…