A. Acernese, C. D. Vecchio, M. Tipaldi, L. Glielmo
{"title":"工业贴标机的状态维护","authors":"A. Acernese, C. D. Vecchio, M. Tipaldi, L. Glielmo","doi":"10.1109/ICSRS48664.2019.8987687","DOIUrl":null,"url":null,"abstract":"This paper reports the outcome of an industrial research on data-driven Condition Based Maintenance (CBM) for the film cutting group of labeling production lines. Objective of the study has been the prediction of erroneous labels cut. The large number of variables involved in thin labels cut (thickness comprised within 30μm and 38 μm) and the high throughput make the prediction of non conforming labels a difficult goal. To this aim, we developed a complete CBM strategy for film cutting groups. To identify failure signature, an exhaustive assessment on indices suggested in literature was done, but none of them were suitable to satisfy problem constraints. Thus we customized the most promising one (namely the root mean square value of the vibration measures) to our setting obtaining notable results. Given the lack of contributions in CBM in thin film cutting, we believe this paper might be of interest for academic researchers or people from industry dealing with similar problems.","PeriodicalId":430931,"journal":{"name":"2019 4th International Conference on System Reliability and Safety (ICSRS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Condition Based Maintenance for Industrial Labeling Machine\",\"authors\":\"A. Acernese, C. D. Vecchio, M. Tipaldi, L. Glielmo\",\"doi\":\"10.1109/ICSRS48664.2019.8987687\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper reports the outcome of an industrial research on data-driven Condition Based Maintenance (CBM) for the film cutting group of labeling production lines. Objective of the study has been the prediction of erroneous labels cut. The large number of variables involved in thin labels cut (thickness comprised within 30μm and 38 μm) and the high throughput make the prediction of non conforming labels a difficult goal. To this aim, we developed a complete CBM strategy for film cutting groups. To identify failure signature, an exhaustive assessment on indices suggested in literature was done, but none of them were suitable to satisfy problem constraints. Thus we customized the most promising one (namely the root mean square value of the vibration measures) to our setting obtaining notable results. Given the lack of contributions in CBM in thin film cutting, we believe this paper might be of interest for academic researchers or people from industry dealing with similar problems.\",\"PeriodicalId\":430931,\"journal\":{\"name\":\"2019 4th International Conference on System Reliability and Safety (ICSRS)\",\"volume\":null,\"pages\":null},\"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 4th International Conference on System Reliability and Safety (ICSRS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSRS48664.2019.8987687\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 4th International Conference on System Reliability and Safety (ICSRS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSRS48664.2019.8987687","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Condition Based Maintenance for Industrial Labeling Machine
This paper reports the outcome of an industrial research on data-driven Condition Based Maintenance (CBM) for the film cutting group of labeling production lines. Objective of the study has been the prediction of erroneous labels cut. The large number of variables involved in thin labels cut (thickness comprised within 30μm and 38 μm) and the high throughput make the prediction of non conforming labels a difficult goal. To this aim, we developed a complete CBM strategy for film cutting groups. To identify failure signature, an exhaustive assessment on indices suggested in literature was done, but none of them were suitable to satisfy problem constraints. Thus we customized the most promising one (namely the root mean square value of the vibration measures) to our setting obtaining notable results. Given the lack of contributions in CBM in thin film cutting, we believe this paper might be of interest for academic researchers or people from industry dealing with similar problems.