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Visual testing: the influence of selected human factors on probability of detection

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To ensure the reliable assessment of components by visual inspection, current standards overemphasise the focus on illuminance as being the only factor of influence. Human factors or an adaptation of viewing conditions to different inspection tasks are not sufficiently considered. In previous investigations, a significant influence of illuminance, testing forged parts with highly reflective surfaces at three different illuminance levels (200 lx, 350 lx and 500 lx), could not be proven. Instead, a more complex system of different influencing factors was indicated. In this work, groups with different human characteristics were compared to investigate the correlations in indication detectability during visual inspection. A questionnaire was used to record various subjectively perceived factors (dissatisfaction, general and lighting scenariospecific disturbance) in the detection of crack-like indications, under three different lighting scenarios. From the factors studied, age, general and specific experience of the participants were found to be the most relevant. General experience in the field of visual inspection, measured in years and frequency of inspections performed in practice, was shown not to have a decisive influence. On the other hand, the influence of specific experience with the test specimen, or comparable components, and the age of the participants seem to have an influence. With increasing age, the probability of detection seems to decrease, while it seems to increase with rising component-specific experience. In the interplay of the factors investigated, specific experience can be influenced most effectively and could thus be increased by intensified and specific practical training. This could have a positive effect on the reliability of visual inspection.

Keywords: HUMAN FACTORS; NON-DESTRUCTIVE TESTING; PROBABILITY OF DETECTION; RELIABILITY; VISUAL INSPECTION

Document Type: Research Article

Affiliations: 1: DGZfP Ausbildung und Training GmbH, Berlin, Germany 2: Applied Validation of NDT, Berlin, Germany 3: Berlin Institute of Technology, Faculty of Transport and Machine Systems, Berlin, Germany

Publication date: 01 January 2023

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