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Automated thermal fuse inspection using machine vision and artificial neural networks
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نویسنده
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Sun Te-Hsiu ,Tien Fang-Cheng ,Tien Fang-Chih ,Kuo Ren-Jieh
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منبع
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journal of intelligent manufacturing - 2016 - دوره : 27 - شماره : 3 - صفحه:639 -651
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چکیده
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Machine vision is an excellent tool for inspecting a variety of items such as textiles, fruit, printed circuit boards, electrical components, labels, integrated circuits, machine tools, etc. this paper presents an intelligent system that incorporates machine vision with artificial intelligent networks to automatically inspect thermal fuses. an effective inspection flow is proposed to detect four commonly seen defects, including black-dot, small-head, bur, and flake during the production of thermal fuses. backpropagation neural networks and learning vector quantization performance is compared in detecting the bur defect because of its illegibility. different numbers of defective samples were screened out from a production line in a case study company and used to demonstrate the efficacy of the proposed system. currently, the proposed inspection system is operating at the case study company, replacing four to six human inspectors. the system not only ensures the quality of the thermal fuses produced, but also reduced the cost of manual visual inspection.
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کلیدواژه
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Thermal fuse ,Machine vision ,Backpropagation neural networks ,LVQ ,Quality control
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آدرس
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Chaoyang University of Technology, Department of Industrial Engineering and Management, ROC, Chung Hua University, ROC, National Taipei University of Technology, Department of Industrial Engineering and Management, ROC, National Taiwan University of Science and Technology, Department of Industrial Management, ROC
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Authors
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