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Assessing the learning curve of human operators under verbal distraction
Assessing the learning curve of human operators under verbal distraction
This research explores how verbal distractions influence the learning process during an assembly task. Participants first practiced a pattern replication task until their performance stabilized, then repeated it under conversation-based distractions. A camera system with ArUco marker tracking and timer-based monitoring was used to assess both accuracy and task completion time. The results showed that while distractions significantly increased task duration, they did not negatively affect the quality of the final product. These findings underline the importance of considering cognitive load in industrial environments and demonstrate the effectiveness of video-based monitoring for evaluating human performance.
Ethical approval number: KEB_MK_RIT_2023_02
The impact of work instruction simplification on operator performance and learning curve efficiency
The impact of work instruction simplification on operator performance and learning curve efficiency
Due to high turnover in industry, efficient onboarding and supportive systems are essential. This research investigates how operators learn a new task and how they interact with different types of work instructions. In a disassembly experiment, we measured task completion time, error rates, and attention to the instructions. Our findings show that simplified work instructions introduced after an initial training phase can significantly reduce task duration without increasing mistakes. These results highlight the potential of instruction abstraction in supporting operator performance during repetitive tasks.
Ethical approval number: 2025-028
Game-based design of human-machine collaboration monitoring system.
Game-based design of human-machine collaboration monitoring system.
Industrial development is evolving towards an increased focus on human-machine collaboration, exemplified by the emergence of Industry 5.0. This new industrial paradigm prioritizes solutions centered around humans and emphasizes resilience and sustainability. A critical aspect of this collaboration is the need for robots to possess more advanced cognitive abilities, allowing for safe co-working environments with humans. Advancements in technology have enabled various methods for monitoring human behavior. Analyzing these behavioral patterns enhances efficiency and collaboration.
My thesis introduces a setting where monitoring the operator and the robot is possible. It is achieved through a camera, an indoor positioning system, and, in the future, wearable sensors. Indicators, for example, the utilization of participants or waiting times, can represent the collaboration.
Measurements were taken with a specific focus, and the results were analyzed comprehensively—the thesis aimed to establish a connection between human activities and collaborative robots while considering human needs. The process used to achieve this objective is demonstrated through two complex games, and the design of experiments, which were then used to create and do more comprehensive experiments, is also presented.
Design of Experiments to evaluate the collaborative work between human and robot
Design of Experiments to evaluate the collaborative work between human and robot
Industrial development is evolving towards an increased focus on human-machine collaboration, exemplified by the emergence of Industry 5.0. This new industrial paradigm prioritizes solutions centered around humans and emphasizes resilience and sustainability. A critical aspect of this collaboration is the need for robots to possess more advanced cognitive abilities, allowing for safe co-working environments with humans. Advancements in technology have enabled various methods for monitoring human behavior. Analyzing these behavioral patterns enhances efficiency and collaboration.
My thesis introduces a setting where monitoring the operator and the robot is possible. It is achieved through a camera, an indoor positioning system, and, in the future, wearable sensors. Indicators, for example, the utilization of participants or waiting times, can represent the collaboration.
Measurements were taken with a specific focus, and the results were analyzed comprehensively—the thesis aimed to establish a connection between human activities and collaborative robots while considering human needs. The process used to achieve this objective is demonstrated through two complex games, and the design of experiments, which were then used to create and do more comprehensive experiments, is also presented.
Mónika Gugolya is supported by the ÚNKP-23-1 new national excellence program of the ministry for culture and innovation from the source of the national research, development and innovation fund.
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