Research on Optimal Design of Visual Elements of CNC Press Display Interface Based on Visual Cognition

With the rapid development of artificial intelligence and computer technology, digital interfaces have become central to CNC press operations. However, effectively presenting complex information within limited display space while reducing cognitive load remains a key challenge. Based on visual cognition theory, this study proposes a cognition-oriented interface optimization framework for CNC press HMIs. User needs were identified through field studies, questionnaires, and interviews and prioritized using the KANO model. A cognitive model linking user perception and interface visual elements was established to guide the interface optimization. Two groups of interface layouts were developed and evaluated through eye-tracking experiments to identify the optimal layout scheme. The selected interface was further refined through visual optimization and validated using usability testing. The results indicate that the optimized interface significantly improved the visual search efficiency, information readability, task completion efficiency, and overall user satisfaction. The proposed framework provides a systematic approach for cognition-driven interface optimization in industrial HMI systems.