Motoharu Tanaka, Takuya Nagata, Yusuke Nishi, S. Arima
{"title":"并行利用资源的生产过程可视化的共同感知与分析——作业车间和流程车间案例","authors":"Motoharu Tanaka, Takuya Nagata, Yusuke Nishi, S. Arima","doi":"10.1109/IIAI-AAI.2018.00134","DOIUrl":null,"url":null,"abstract":"This paper presented a common system of the automated sensing and analysis for major 2 types of manufacturing format; the flow-shop type and the job-shop type. About sensing, electrical signal from production equipment and/or tools were the main target of a general-purpose sensing. In particular, applications of a data logger are introduced. About analysis, discussion in this paper was focused on the classification of status of production resource, detection of its change in time-series, and so on. Some quantitative analyses, such a clustering , are required to be combined. In addition, the key performance indicator (KPI) was also developed for better visualization. We present KPI of “throughput yield” for the flow-shop, and \"Parallel utilization index (PUI)\" for the job-shop. All those have been evaluated by some numerical experiments for small and middle-sized companies of the Ibaraki IoT-Robot study group.","PeriodicalId":309975,"journal":{"name":"2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Common Sensing and Analyses to Visualize a Production Process with Parallelly Utilized Resource - Job-Shop and Flow-Shop Cases\",\"authors\":\"Motoharu Tanaka, Takuya Nagata, Yusuke Nishi, S. Arima\",\"doi\":\"10.1109/IIAI-AAI.2018.00134\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presented a common system of the automated sensing and analysis for major 2 types of manufacturing format; the flow-shop type and the job-shop type. About sensing, electrical signal from production equipment and/or tools were the main target of a general-purpose sensing. In particular, applications of a data logger are introduced. About analysis, discussion in this paper was focused on the classification of status of production resource, detection of its change in time-series, and so on. Some quantitative analyses, such a clustering , are required to be combined. In addition, the key performance indicator (KPI) was also developed for better visualization. We present KPI of “throughput yield” for the flow-shop, and \\\"Parallel utilization index (PUI)\\\" for the job-shop. All those have been evaluated by some numerical experiments for small and middle-sized companies of the Ibaraki IoT-Robot study group.\",\"PeriodicalId\":309975,\"journal\":{\"name\":\"2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IIAI-AAI.2018.00134\",\"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 7th International Congress on Advanced Applied Informatics (IIAI-AAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIAI-AAI.2018.00134","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Common Sensing and Analyses to Visualize a Production Process with Parallelly Utilized Resource - Job-Shop and Flow-Shop Cases
This paper presented a common system of the automated sensing and analysis for major 2 types of manufacturing format; the flow-shop type and the job-shop type. About sensing, electrical signal from production equipment and/or tools were the main target of a general-purpose sensing. In particular, applications of a data logger are introduced. About analysis, discussion in this paper was focused on the classification of status of production resource, detection of its change in time-series, and so on. Some quantitative analyses, such a clustering , are required to be combined. In addition, the key performance indicator (KPI) was also developed for better visualization. We present KPI of “throughput yield” for the flow-shop, and "Parallel utilization index (PUI)" for the job-shop. All those have been evaluated by some numerical experiments for small and middle-sized companies of the Ibaraki IoT-Robot study group.