• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.729-735
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• 2021

Recently Artificial Intelligence(AI) has been developed and used in various fields. Especially AI recognition technology can perceive and distinguish images so it should plays a significant role in quality inspection process. For stability of autonomous driving technology, semiconductors inside automobiles must be protected from external electromagnetic wave(EM wave). As a shield film, a thin polymeric material with hole shaped micro-patterns created by a laser processing could be used for the protection. The shielding efficiency of the film can be increased by the hole structure with appropriate pitch and size. However, since the sensitivity of micro-machining for some parameters, the shape of every single hole can not be same, even it is possible to make defective patterns during process. And it is absolutely time consuming way to inspect all patterns by just using optical microscope. In this paper, we introduce a AI inspection system which is based on web site AI tool. And we evaluate the usefulness of AI model by calculate Area Under ROC curve(Receiver Operating Characteristics). The AI system can classify the micro-patterns into normal or abnormal ones displaying the text of the result on real-time images and save them as image files respectively. Furthermore, pressing the running button, the Hardware of robot arm with two Arduino motors move the film on the optical microscopy stage in order for raster scanning. So this AI system can inspect the entire micro-patterns of a film automatically. If our system could collect much more identified data, it is believed that this system should be a more precise and accurate process for the efficiency of the AI inspection. Also this one could be applied to image-based inspection process of other products.

• Journal of the Korea Institute of Building Construction
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• v.23 no.6
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• pp.663-671
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• 2023

This research experimentally evaluated the recyclability of four varieties of lignocellulosic fly ash(FA), a by-product from three power plants employing lignocellulosic biomass(Bio-SRF, wood pellets) as a fuel source. Comprehensive analyses were conducted on FA, encompassing both physical parameters (particle shape, size distribution, fineness, and density) and chemical properties(chemical composition and heavy metal content). Mortar test specimens, with FA mixing ratios ranging from 5 to 20%, were produced in compliance with KS L 5405 standards, and their flow and compressive strength were subsequently measured. The test results indicated that the four types of FA exhibited particle sizes approximately between 20~30㎛, densities around 2.3~2.5g/cm³, and a fineness range of 2,600~4,900cm²/g. The FA comprised approximately 50~90% of components such as SiO₂, Al₂O₃, Fe₂O₃, and CaO, displaying characteristics akin to type-II and type-III FA of KS L 5405 standards, albeit with differences in chlorine and SiO₂ content. From the mortar tests, it was observed that the compressive strength of the mortar ranged between 34~47MPa when the pellet combustion FA was mixed in proportions of 5~20%. FA, produced exclusively from the combustion of 100% lignocellulosic fuel, is assessed to possess high recyclability potential as a substitute for conventional admixtures.