ArticleSensors (Basel, Switzerland)2025
Adaptive Augmented Reality User Interfaces for Real-Time Defect Visualization and On-the-Fly Reconfiguration for Zero-Defect Manufacturing.
Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Zero-defect manufacturing is one of the most promising strategies to mitigate failures within manufacturing processes, allowing industries to increase product quality efficiently and effectively. One of the challenges faced in the practical adoption of zero-defect manufacturing is that the most important aspect of manufacturing, people, is often neglected. Aiming to support shop floor operators, this work introduces a human-centric approach assisting them to become aware of defects in the production line and imminently reconfigure it. Our system comprises an Augmented Reality application that encompasses interfaces that dynamically adapt to different contexts of use and enable operators to interact naturally and effectively and reconfigure the manufacturing process. The system leverages the efficiency of the shop floor operators in monitoring and controling the production line they are working on, according to the task they are performing, and their level of expertise, to produce appropriate visual components. To demonstrate the versatility and generality of the proposed system we evaluated it in three different production lines, conducting cognitive walkthroughs with experts and user-based evaluations with thirty shop floor operators. The results demonstrate that the system is intuitive and user-friendly, facilitating operator engagement and situational awareness, enhancing operator attentiveness, and achieving improved operational outcomes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.