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To prevent outflow of defective products to customers, many manufacturing industries have focused not only on processing and assembling, but also on product inspection. In appearance inspection, a work support system using deep learning has been proposed, and its usefulness was experimentally shown in model images of industrial product in recent years. Therefore, in this study, aiming for practical application of work support system, the relationship between the lighting angles and the visibility of defects is experimentally evaluated using 80 actual automobile parts as a case study. As results, it is found that the visibility of the defect greatly differs depending on the angle of lighting, and the conditions for high visibility differ depending on the defect. Furthermore, it is found that it is possible to improve the visibility of defects in about 24% of all 80 automobile parts, but, it is difficult to improve the visibility of defects for the remaining 76%. From the above, for the practical application of the work support system, it is clarified that the importance of constructing of lighting condition optimization method to improve the visibility of defects, and examining the input image considering the visibility of defects for deep learning.

The electronic properties of the perovskite oxide SrCu3Fe4O12 subjected to pressure in a diamond anvil cell were investigated by 57Fe Mossbauer spectroscopy and electrical resistance measurements. ...

The intersite charge transfer at room temperature was found to occur by applying pressure in the A-site-ordered double-perovskite-structure oxide LaCu3Fe4O12. The pressure-induced charge transfer b...