Automated Label Quality Control in Industry 4.0

Automated Label Quality Control in Industry 4.0

연구 분야: Software Development

학회: Asian Conference on Intelligent Information and Database Systems

Enhancing industrial quality control is an ultimate objective, and it can be significantly elevated through the integration of cutting-edge technological innovations. One such innovation is the application of machine vision technology, which offers a dependable and rapid method for continuous inspection, thereby bolstering manufacturers’ operational efficiency. Machine vision equipment generates valuable data, facilitating the identification and reporting of defective products and preventing the further production of scrap items. In the context of this study, the quality control model for product printing plays a crucial role in identifying flawed prints, thereby mitigating the wastage that typically occurs within a given facility. Defectively printed pieces lack the potential for rectification and are consequently discarded. This article elucidates the entire process, encompassing data collection, data analysis, and the feedback mechanism. Furthermore, the article conducts a comparative examination of image editing concerning the resulting quality of processing. The outcomes of this research clearly demonstrate that the proposed model satisfactorily meets the required standards and offers practical advantages in the realm of industrial quality control.