{"title":"装配机视觉检测系统的开发","authors":"Jeonghong Kim","doi":"10.1109/ICUFN.2018.8436961","DOIUrl":null,"url":null,"abstract":"In a factory that assembles various devices, functional inspection and visual inspection are carried out before the product is shipped out. Most functional tests are done automatically through the system, whereas visual inspection is done by the human eyes. Human remember what they have just seen before, and it is difficult to detect the failure of a similar assembly device. Even if the function of the assembling device is satisfied, there is a problem in the reliability of the quality control due to the appearance error. Various image processing techniques have been developed to solve this problem. In this paper, we proposed a method to improve the accuracy of error detection by applying the CNN model to the external inspection of the assembling device.","PeriodicalId":224367,"journal":{"name":"2018 Tenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Development of Visual Inspection System for Assembly Machine\",\"authors\":\"Jeonghong Kim\",\"doi\":\"10.1109/ICUFN.2018.8436961\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In a factory that assembles various devices, functional inspection and visual inspection are carried out before the product is shipped out. Most functional tests are done automatically through the system, whereas visual inspection is done by the human eyes. Human remember what they have just seen before, and it is difficult to detect the failure of a similar assembly device. Even if the function of the assembling device is satisfied, there is a problem in the reliability of the quality control due to the appearance error. Various image processing techniques have been developed to solve this problem. In this paper, we proposed a method to improve the accuracy of error detection by applying the CNN model to the external inspection of the assembling device.\",\"PeriodicalId\":224367,\"journal\":{\"name\":\"2018 Tenth International Conference on Ubiquitous and Future Networks (ICUFN)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Tenth International Conference on Ubiquitous and Future Networks (ICUFN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICUFN.2018.8436961\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Tenth International Conference on Ubiquitous and Future Networks (ICUFN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICUFN.2018.8436961","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development of Visual Inspection System for Assembly Machine
In a factory that assembles various devices, functional inspection and visual inspection are carried out before the product is shipped out. Most functional tests are done automatically through the system, whereas visual inspection is done by the human eyes. Human remember what they have just seen before, and it is difficult to detect the failure of a similar assembly device. Even if the function of the assembling device is satisfied, there is a problem in the reliability of the quality control due to the appearance error. Various image processing techniques have been developed to solve this problem. In this paper, we proposed a method to improve the accuracy of error detection by applying the CNN model to the external inspection of the assembling device.
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