Usability and User Experience in an Industrial Metaverse: A Mixed-Methods Study of the Necoverse Point Cloud Inspection System for Shipbuilding

Industrial metaverse systems enable shared, immersive environments for coordinating complex, data-intensive industrial workflows; however, ensuring effective and usable interaction remains a key barrier to professional adoption. This study examines immersive point cloud- and CAD-based inspection tasks in an industrial metaverse context using a mixed-methods evaluation that combines perceived usability ratings, cognitive workload assessment (NASA-TLX), validated presence and flow instruments, qualitative interviews, and structured observation. The results indicate that users generally experienced smooth navigation, manageable cognitive workload, and a meaningful sense of spatial presence, supporting focused and task-oriented engagement. At the same time, execution-level challenges—particularly related to tool discoverability, annotation flexibility, system feedback clarity, and interaction ergonomics—introduced workflow friction for some users. By triangulating quantitative, qualitative, and observational evidence, the study derives actionable design recommendations, including adaptive onboarding, improved feedback mechanisms, and refinements to interaction design. Overall, the findings provide empirical insight into how usability, cognitive workload, presence, and flow jointly shape user experience in industrial metaverse inspection environments and inform the development of more robust, user-centered industrial systems.