The Internet technology for defect detection system with deep learning method in smart factory

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The most obvious difference between the recent smart factory and the traditional automation factory is that the techniques about internet of thing (IoT) are introduced. The smart factory that employs IoT techniques intelligently manages the automated manufacturing equipment and automated defect detection equipment to improve production efficiency and quality significantly. The equipments used in the smart factory are manufacturing equipments, functional testing equipment and defect detection equipment. Defect detection equipment, mainly in the entire product manufacturing and packaging and functional testing process, the establishment of checkpoints, phased detection of semi-finished products to identify defective and defective products selected. As a result, the defective product no longer goes through all of the following processes, thus reducing costs and improving the yield of the final product shipped. In the development of classification algorithm, a huge breakthrough has been made in the deep learning algorithm in recent years. Therefore, in recent years, many studies have tried to apply deep learning algorithm to various fields. However, most of the current studies focus on the performance of the deep learning algorithm in their applications. Fewer studies research the environmental design for the system employing deep learning algorithm. For example, the network architecture for the system employing deep learning algorithm is less discussed by studies. Therefore, this study presents a architecture of smart factory which employing deep learning algorithm in defect detection system. Thereafter, this study presents the network architecture for the proposed smart factory. Finally, the internet technology for defect detection system with deep learning method in smart factory is presented.