Cognitive digital twin in manufacturing process: integrating the knowledge graph for enhanced human-centric Industry 5.0

Industry 5.0 emphasises human-centric intelligent manufacturing, posing challenges in integrating human expertise with advanced machine capabilities. To address these challenges, a novel three-layer cognitive digital twin model based on knowledge graphs is proposed, designed to integrate workers' knowledge and experience into intelligent manufacturing processes. This model comprises three layers: an ontology layer that constructs a foundational process knowledge ontology library; a knowledge layer that maps real-time data to dynamically update digital models; and a cognitive layer that utilises machine learning, knowledge reasoning, and knowledge mining for advanced analysis, state understanding, and model evolution. The model promotes user interaction through intuitive interfaces and a Q&A system, leveraging techniques such as knowledge reasoning and querying to support decision-making and enhance worker engagement. Validated through a system implemented for aero-engine blade production, this cognitive digital twin model leverages human expertise and machine capabilities to enhance process control, quality management, and overall efficiency. The proposed approach demonstrates significant potential for advancing personalised human-machine interaction in manufacturing, truly embodying the value of a human-centric approach and paving the way for future developments in the field.