QUAN LIU, Aiming Liu, Yuanming Li, Wenjun Xu, Jiayi Liu, Gaobo Chen, Wei Dai
{"title":"Intelligent condition perception network towards sustainable manufacturing capability for manufacturing systems","authors":"QUAN LIU, Aiming Liu, Yuanming Li, Wenjun Xu, Jiayi Liu, Gaobo Chen, Wei Dai","doi":"10.1504/IJMR.2017.10006341","DOIUrl":null,"url":null,"abstract":"Sustainability has become an important factor from which we can judge the performance of modern manufacturing systems. The condition perception of sustainable manufacturing capability (SMC) can provide reliable manufacturing information and data support for manufacturing systems. This paper proposes an intelligent condition perception network (ICPN) for SMC of manufacturing systems, which focuses on the production condition monitoring, the energy consumption metering, and the perception data transfer. The proposed hybrid wireless perception network consists of the embedded Radio Frequency Identification (RFID) perception modules, embedded energy consumption perception modules and environment perception modules. In view of the several heterogeneous networks might coexist in the manufacturing environment, the heterogeneous networks adaptation device is designed to figure out the problem of differences of data transmission in heterogeneous networks. Finally, a prototype system is deployed in a laboratory environment. The experimental results demonstrate that the system can satisfy the requirements of condition perception for SMC.","PeriodicalId":154059,"journal":{"name":"Int. J. Manuf. Res.","volume":"78 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Manuf. Res.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJMR.2017.10006341","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Sustainability has become an important factor from which we can judge the performance of modern manufacturing systems. The condition perception of sustainable manufacturing capability (SMC) can provide reliable manufacturing information and data support for manufacturing systems. This paper proposes an intelligent condition perception network (ICPN) for SMC of manufacturing systems, which focuses on the production condition monitoring, the energy consumption metering, and the perception data transfer. The proposed hybrid wireless perception network consists of the embedded Radio Frequency Identification (RFID) perception modules, embedded energy consumption perception modules and environment perception modules. In view of the several heterogeneous networks might coexist in the manufacturing environment, the heterogeneous networks adaptation device is designed to figure out the problem of differences of data transmission in heterogeneous networks. Finally, a prototype system is deployed in a laboratory environment. The experimental results demonstrate that the system can satisfy the requirements of condition perception for SMC.