Intelligent maintenance for industrial processes, a case study on cold stamping

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dc.contributor.authorBoto, Fernando
dc.contributor.authorLizuain, Zigor
dc.contributor.authorCortadi, Alberto Jimenez
dc.contributor.editorPerez Garcia, Hilde
dc.contributor.editorAlfonso-Cendon, Javier
dc.contributor.editorSanchez Gonzalez, Lidia
dc.contributor.editorCorchado, Emilio
dc.contributor.editorQuintian, Hector
dc.contributor.institutionTecnalia Research & Innovation
dc.contributor.institutionFACTORY
dc.date.accessioned2024-07-24T11:55:05Z
dc.date.available2024-07-24T11:55:05Z
dc.date.issued2018
dc.descriptionPublisher Copyright: © 2018, Springer International Publishing AG.
dc.description.abstractThe correct diagnosis of tool breakage is fundamental to improve productivity, minimizing the number of unproductive hours and avoiding expensive repairs. The use of Data Mining techniques provides a significant added value in terms of improvements in the robustness, reliability and flexibility of the monitored systems. In this work, a general view of a diagnosis and prognosis of tool breakage in Industrial Processes is proposed. The important issues identified will be analyzed: filtering, process characterization and data based modeling. A case study has been implemented to carry out the prognosis of tool breakage in the cold stamping process. The results provided are qualitative trends and hypothesis to perform the prognosis. Although a validation in real operation is needed, these results are promising and demonstrate the goodness of using these type of techniques in real processes.en
dc.description.statusPeer reviewed
dc.format.extent10
dc.identifier.citationBoto , F , Lizuain , Z & Cortadi , A J 2018 , Intelligent maintenance for industrial processes, a case study on cold stamping . in H Perez Garcia , J Alfonso-Cendon , L Sanchez Gonzalez , E Corchado & H Quintian (eds) , International Joint Conference SOCO’17- CISIS’17-ICEUTE’17, Proceedings . Advances in Intelligent Systems and Computing , vol. 649 , Springer Verlag , pp. 157-166 , International Joint Conference on 12th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2017, 10th International Conference on Computational Intelligence in Security for Information Systems, CISIS 2017 and 8th International Conference on European Transnational Education, ICEUTE 2017 , Leon , Spain , 6/09/17 . https://doi.org/10.1007/978-3-319-67180-2_15
dc.identifier.citationconference
dc.identifier.doi10.1007/978-3-319-67180-2_15
dc.identifier.isbn9783319671796
dc.identifier.issn2194-5357
dc.identifier.urihttps://hdl.handle.net/11556/2474
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85028642214&partnerID=8YFLogxK
dc.language.isoeng
dc.publisherSpringer Verlag
dc.relation.ispartofInternational Joint Conference SOCO’17- CISIS’17-ICEUTE’17, Proceedings
dc.relation.ispartofseriesAdvances in Intelligent Systems and Computing
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsCold stamping
dc.subject.keywordsData mining
dc.subject.keywordsFault diagnosis
dc.subject.keywordsTime series analysis
dc.subject.keywordsControl and Systems Engineering
dc.subject.keywordsGeneral Computer Science
dc.titleIntelligent maintenance for industrial processes, a case study on cold stampingen
dc.typeconference output
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