Engelbert Harsandi Erik Suryadarma, T. J. Ai, P. Anggoro
{"title":"Value Analysis of Predictive Maintenance in Cooling System of a Die Casting Process by Data SCADA","authors":"Engelbert Harsandi Erik Suryadarma, T. J. Ai, P. Anggoro","doi":"10.1109/ICST50505.2020.9732888","DOIUrl":null,"url":null,"abstract":"The cooling system is vital for the die casting process. The problematic cooling system will make the process of solidification uncontrolled. So that maintenance (especially predictive maintenance) is needed to keep the cooling system in good condition. However, the application of predictive maintenance requires complex resources. This research will simplify the predictive maintenance procedure on the cooling system in the casting process by reducing the number of sensors and calculations. This research uses SCADA technology and Machine Learning to keep getting accurate predictions. Based on the test results, the level of complexity of the proposed predictive maintenance system is more straightforward than before the value analysis was carried out, but has an accuracy level equivalent to before the value analysis applied.","PeriodicalId":125807,"journal":{"name":"2020 6th International Conference on Science and Technology (ICST)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 6th International Conference on Science and Technology (ICST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICST50505.2020.9732888","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
The cooling system is vital for the die casting process. The problematic cooling system will make the process of solidification uncontrolled. So that maintenance (especially predictive maintenance) is needed to keep the cooling system in good condition. However, the application of predictive maintenance requires complex resources. This research will simplify the predictive maintenance procedure on the cooling system in the casting process by reducing the number of sensors and calculations. This research uses SCADA technology and Machine Learning to keep getting accurate predictions. Based on the test results, the level of complexity of the proposed predictive maintenance system is more straightforward than before the value analysis was carried out, but has an accuracy level equivalent to before the value analysis applied.