The objective of this project is to design a digital twin monitoring interface that visualizes real-time factory operations, machine health, and predictive maintenance alerts. The interface should simplify complex industrial data and support quick decision-making for plant managers.
Research digital twin technology and industrial monitoring systems.
Identify personas such as plant managers and maintenance engineers.
Map workflows for monitoring machine performance and fault detection.
Analyze challenges in understanding technical operational data.
Design low-fidelity wireframes representing 3D factory layouts and machine nodes.
Create interaction patterns for zooming, filtering, and viewing maintenance logs.
Develop high-fidelity dashboard prototypes with predictive alert indicators.
Incorporate color-coded status systems for risk visualization.
Conduct usability testing focusing on clarity under time-sensitive conditions.
Refine data grouping to reduce cognitive overload.
Document industrial UX standards and system performance metrics.
