{"title":"A Prefatory Study on Data Channelling Mechanism towards Industry 4.0","authors":"Kheng Hui Ng, Y. Tew, M. Yip","doi":"10.1109/APSIPAASC47483.2019.9023089","DOIUrl":null,"url":null,"abstract":"Data are increasing in volume, variety and velocity in this Internet of things and big data era. It applies from industry (or manufacturing) process monitoring control to video surveillance analysis to track human and machines activities. Therefore, fast and accurate approaches in data channelling are needed to effectively deal with these big data. This paper presents practical methods to manage and transfer the data from industry manufacturing site to a centralized data processing hub. In this hub, data are transformed into understandable information, which can assist human in understanding and monitoring manufacturing situation autonomously. These data are collected and channelled to desired location for analysis through Open Platform Communication Unified Architecture (OPC UA). Industrial protocols and standards are used to interpret the data channelling methods and tested on several industrial machines. Result shows that size of data and number of OPC UA Client that connects to OPC Server affects the data channelling speed,","PeriodicalId":145222,"journal":{"name":"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSIPAASC47483.2019.9023089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Data are increasing in volume, variety and velocity in this Internet of things and big data era. It applies from industry (or manufacturing) process monitoring control to video surveillance analysis to track human and machines activities. Therefore, fast and accurate approaches in data channelling are needed to effectively deal with these big data. This paper presents practical methods to manage and transfer the data from industry manufacturing site to a centralized data processing hub. In this hub, data are transformed into understandable information, which can assist human in understanding and monitoring manufacturing situation autonomously. These data are collected and channelled to desired location for analysis through Open Platform Communication Unified Architecture (OPC UA). Industrial protocols and standards are used to interpret the data channelling methods and tested on several industrial machines. Result shows that size of data and number of OPC UA Client that connects to OPC Server affects the data channelling speed,