RT Conference Proceedings
T1 Intelligent maintenance for industrial processes, a case study on cold stamping
A1 Boto, Fernando
A1 Lizuain, Zigor
A1 Cortadi, Alberto Jimenez
A2 Perez Garcia, Hilde
A2 Alfonso-Cendon, Javier
A2 Sanchez Gonzalez, Lidia
A2 Corchado, Emilio
A2 Quintian, Hector
AB The 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.
PB Springer Verlag
SN 9783319671796
SN 2194-5357
YR 2018
FD 2018
LK https://hdl.handle.net/11556/2474
UL https://hdl.handle.net/11556/2474
LA eng
NO Boto , 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
NO conference
NO Publisher Copyright: © 2018, Springer International Publishing AG.
DS TECNALIA Publications
RD 30 jul 2024