Gugolya, Mónika and Medvegy, Tibor and Abonyi, János and Ruppert, Tamás (2025) Assessing the Learning Curve of Human Operators Under Verbal Distraction. IET COLLABORATIVE INTELLIGENT MANUFACTURING, 7 (1). No. e70038. ISSN 2516-8398
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 | Text IET Collab Intel Manufact - 2025 - Gugolya - Assessing the Learning Curve of Human Operators Under Verbal Distraction.pdf - Published Version Available under License Creative Commons Attribution. Download (1MB) | Preview | 
Abstract
This study investigates the learning curve in an assembly process under distraction, highlighting the use of video-based monitoring to evaluate changes in human performance over time. The experimental setup involving camera- and timer-based monitoring to evaluate operator performance in different metrics, including time-based indicators and accuracy of the assembled product. Participants were tasked with replicating patterns until they got a flat learning curve without any distractions during the process. After learning the process, they were also asked to repeat the task with conversation-based distractions to assess its influence during the main task. In our developed framework, an ArUco marker-based video recognition enabled the accuracy assessment. Statistical analyses of the collected data provided insight into performance variations. The study evaluates changes in the learning curve during verbal distraction, highlighting the need to understand and consider its effect during the process. The experiments revealed significant effects of distraction on the completion time, but the camera-based recognition system showed no notable decline in work quality.
| Item Type: | Article | 
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| Uncontrolled Keywords: | distraction , human computer interaction , human performance , learning curve , manufacturing systems | 
| Subjects: | T Technology / alkalmazott, műszaki tudományok > T2 Technology (General) / műszaki tudományok általában | 
| Depositing User: | Dr. Tamás Ruppert | 
| Date Deposited: | 25 Sep 2025 05:55 | 
| Last Modified: | 25 Sep 2025 05:55 | 
| URI: | https://real.mtak.hu/id/eprint/225254 | 
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