Ricardo Silva Peres, A. Rocha, J. Matos-Carvalho, J. Barata
{"title":"GO0DMAN Data Model - Interoperability in Multistage Zero Defect Manufacturing","authors":"Ricardo Silva Peres, A. Rocha, J. Matos-Carvalho, J. Barata","doi":"10.1109/INDIN.2018.8472017","DOIUrl":null,"url":null,"abstract":"In the last decades, several research initiatives suggested new solutions regarding the interoperability and interconnectivity among heterogeneous production components and all the actors that somehow interact within the shop-floor. However, most of the proposed data representations are focused on the description of the production capabilities. In this paper, it is proposed a common data model focused not only in the production capabilities of the different components as well as the description of all the events, variables and resources that could indicate quality issues. Hence, the proposed data model describes all the information required by the GO0DMAN solution to reduce as much as possible, the defects, the respective causes and the strategies to avoid the propagation along the line. In order to increase the adoption of the proposed data model, it was developed using AutomationML. The proposed data model was designed and tested within the scope of the Horizon 2020 GO0DMAN project.","PeriodicalId":6467,"journal":{"name":"2018 IEEE 16th International Conference on Industrial Informatics (INDIN)","volume":"150 1","pages":"815-821"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 16th International Conference on Industrial Informatics (INDIN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDIN.2018.8472017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
In the last decades, several research initiatives suggested new solutions regarding the interoperability and interconnectivity among heterogeneous production components and all the actors that somehow interact within the shop-floor. However, most of the proposed data representations are focused on the description of the production capabilities. In this paper, it is proposed a common data model focused not only in the production capabilities of the different components as well as the description of all the events, variables and resources that could indicate quality issues. Hence, the proposed data model describes all the information required by the GO0DMAN solution to reduce as much as possible, the defects, the respective causes and the strategies to avoid the propagation along the line. In order to increase the adoption of the proposed data model, it was developed using AutomationML. The proposed data model was designed and tested within the scope of the Horizon 2020 GO0DMAN project.