Intelligent assembly support systems for human-centric manufacturing: A survey

This survey provides a structured analysis of intelligent assembly support systems, examining how these systems perceive tasks, reason about assembly processes, generate support actions, and interact with human operators in complex industrial environments. A systematic literature review of 184 publications from 2015 to 2026 was conducted, combining thematic analysis with bibliometric and temporal analyses to identify research trends, technological developments, and persistent challenges across perception, reasoning, interaction, and deployment. The analysis is structured around three perspectives: perception and task understanding under uncertain industrial conditions, adaptive support for heterogeneous workers, and emerging technologies with implications for industrial deployment. The review reveals that current systems remain predominantly focused on vision-based perception, action recognition, and predefined support strategies, with limited consideration of perception uncertainty arising from visual ambiguity and environmental changes, variations in human assembly behaviour, and diverse worker capabilities and support needs. By synthesising fragmented research streams across technical, human, and deployment perspectives, this survey identifies a fundamental transition from recognition-oriented support tools towards uncertainty-aware decision-support systems that enable adaptive human–AI collaboration. Key challenges include robust perception under environmental and visual variability, adaptive support for heterogeneous workers, trustworthy integration of emerging technologies, such as large language models and human-centric digital twins, and practical requirements for industrial deployment. This review establishes a broader perspective for evaluating intelligent assembly support systems, proposing that future progress should be assessed not only through technical performance but also through adaptability, trust calibration, human autonomy, and long-term operational viability. The findings provide a roadmap for Industry 5.0 assembly environments in which intelligent systems augment rather than replace human expertise.