Hugo O. Garcés, Eduardo Morales, Eduardo Espinosa, H. Cabrera, A. Rojas, Luis E. Arias, Paulo Rivera, G. Carvajal, A. Fuentes
{"title":"Data analytics tools by alarms visualization and artificial intelligence applied in industrial monitoring","authors":"Hugo O. Garcés, Eduardo Morales, Eduardo Espinosa, H. Cabrera, A. Rojas, Luis E. Arias, Paulo Rivera, G. Carvajal, A. Fuentes","doi":"10.1109/ICAACCA51523.2021.9465320","DOIUrl":null,"url":null,"abstract":"In process industries, the availability of large volumes of data is not directly related to the extraction of valuable information or process monitoring with good performance. Usually, data is directly visualized as tables or tendency graphics, being not used properly. This paper presents the design of process monitoring by considering the design of alarms visualization plots which provides useful information in a unique plot, combined with soft sensor design used for the prediction of critical variables which defines the process operational performance. Examples of two cases with real industrial data are provided to demonstrate the effectiveness and utility of these methods.","PeriodicalId":328922,"journal":{"name":"2021 IEEE International Conference on Automation/XXIV Congress of the Chilean Association of Automatic Control (ICA-ACCA)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Automation/XXIV Congress of the Chilean Association of Automatic Control (ICA-ACCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAACCA51523.2021.9465320","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
In process industries, the availability of large volumes of data is not directly related to the extraction of valuable information or process monitoring with good performance. Usually, data is directly visualized as tables or tendency graphics, being not used properly. This paper presents the design of process monitoring by considering the design of alarms visualization plots which provides useful information in a unique plot, combined with soft sensor design used for the prediction of critical variables which defines the process operational performance. Examples of two cases with real industrial data are provided to demonstrate the effectiveness and utility of these methods.