Adaptive Graphic Interaction Model: A Mixed-Method Framework for Future Factory Design

This study investigates the role of visual interfaces in enhancing human-machine interaction in high-tech factory environments. The research focuses on the Adaptive Graphical Interaction Model (AGIM), which integrates graphic design principles with adaptive visual interactions to support context-sensitive user tasks. A mixed-methods approach was employed: domain specialists were interviewed, and experimental lab tests of prototype interfaces were conducted to measure user experience, cognitive load, and visual usability. Quantitative metrics from UX tools and qualitative coding of observed behavior were used to assess performance under different simulated operating conditions. Results indicate that AGIM reduces cognitive load by 18% on average and improves task efficiency by 12% compared to static interfaces, supporting the practical effectiveness of adaptive visual systems. The findings also suggest that context-sensitive graphical adaptations enhance intuitive navigation and user engagement. Overall, AGIM provides both conceptual guidance for interface design and practical applications for engineers and designers aiming to develop adaptive, context-aware visual systems in industrial settings. The study is framed as an exploratory design investigation, highlighting potential rather than asserting definitive claims.