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- W4378192008 abstract "Industry 4.0 is the ongoing automation of conventional manufacturing and industrial applications using smart technology. Quality control (QC) is a set of procedures to ensure that a manufactured product adheres to a defined set of quality criteria or meets the requirements of the customer. Many applications within the manufacturing domain employ image-processing or machine learning systems but deep learning-based applications are rare. The goal of this project is to leverage deep learning methods for the automation of quality control. A visual QC automation application is proposed that utilizes a camera placed over a product assembly line containing 3-D printed product samples in a smart factory prototype setup for data collection. After model training, the model will perform object detection and recognition for analyzing complex free-form products and perform product dimension and surface analysis to identify the products that meet the quality control guidelines." @default.
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- W4378192008 date "2023-04-17" @default.
- W4378192008 modified "2023-09-30" @default.
- W4378192008 title "Application of Automated Quality Control in Smart Factories - A Deep Learning-based Approach" @default.
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- W4378192008 doi "https://doi.org/10.1109/syscon53073.2023.10131100" @default.
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