CC BY 4.0Lentes, JoachimJoachimLentesSaba Gayoso, Christian OswaldoChristian OswaldoSaba GayosoLück, MatthiasMatthiasLückHölzle, KatharinaKatharinaHölzle2025-11-262025-11-262025-09https://publica.fraunhofer.de/handle/publica/499767https://doi.org/10.24406/publica-657410.30844/I4SE.25.5.610.24406/publica-6574Industrial companies in Germany face demographic change and stagnating productivity in an increasingly complex world. Manual assembly remains essential for complex, low-volume products, yet productivity and quality lag due to human variability. This paper introduces a concept and demonstrator for an empathic assembly assistance system that merges a human digital twin and AI-based screwdriver data analytics within a modular architecture. Tightening anomalies are classified, linked to inferred worker states and translated into information and recommendations.enassemblydigitalizationassistance systemdigital twinpose recognitionempathic technical systemsontology-based systemsjournal article