A hybrid machine learning approach for predictive maintenance in smart factories of the future

Sangje Cho; Gökan May; Ioannis Tourkogiorgis; Roberto Perez; Oscar Lazaro; Borja de la Maza; Dimitris Kiritsis

doi:10.1007/978-3-319-99707-0_39

A hybrid machine learning approach for predictive maintenance in smart factories of the future

Sangje Cho, Gökan May, Ioannis Tourkogiorgis, Roberto Perez, Oscar Lazaro, Borja de la Maza, Dimitris Kiritsis

Icole Polytechnique Fédérale de Lausanne

Research output: Chapter or Contribution to Book › Literary contribution

Original language	English
Title of host publication	Advances in Production Management Systems. Smart Manufacturing for Industry 4.0 - IFIP WG 5.7 International Conference, APMS 2018, Proceedings
Editors	Gregor von Cieminski, Dimitris Kiritsis, Ilkyeong Moon, Jinwoo Park, Gyu M. Lee
Pages	311-317
Number of pages	7
DOIs	https://doi.org/10.1007/978-3-319-99707-0_39
State	Published - 2018
Externally published	Yes
Event	IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2018 - Seoul, Korea, Republic of Duration: Aug 26 2018 → Aug 30 2018

Publication series

Name	IFIP Advances in Information and Communication Technology
Volume	536
ISSN (Print)	1868-4238

Conference

Conference	IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2018
Country/Territory	Korea, Republic of
City	Seoul
Period	8/26/18 → 8/30/18

ASJC Scopus Subject Areas

Information Systems
Computer Networks and Communications
Information Systems and Management

Keywords

Asset management
Big data
Industry 4.0
Machine learning
Predictive maintenance
Smart factories
Sustainable manufacturing

Access to Document

10.1007/978-3-319-99707-0_39

Cite this

Cho, S., May, G., Tourkogiorgis, I., Perez, R., Lazaro, O., de la Maza, B., & Kiritsis, D. (2018). A hybrid machine learning approach for predictive maintenance in smart factories of the future. In G. von Cieminski, D. Kiritsis, I. Moon, J. Park, & G. M. Lee (Eds.), Advances in Production Management Systems. Smart Manufacturing for Industry 4.0 - IFIP WG 5.7 International Conference, APMS 2018, Proceedings (pp. 311-317). (IFIP Advances in Information and Communication Technology; Vol. 536). https://doi.org/10.1007/978-3-319-99707-0_39

A hybrid machine learning approach for predictive maintenance in smart factories of the future. / Cho, Sangje; May, Gökan; Tourkogiorgis, Ioannis et al.
Advances in Production Management Systems. Smart Manufacturing for Industry 4.0 - IFIP WG 5.7 International Conference, APMS 2018, Proceedings. ed. / Gregor von Cieminski; Dimitris Kiritsis; Ilkyeong Moon; Jinwoo Park; Gyu M. Lee. 2018. p. 311-317 (IFIP Advances in Information and Communication Technology; Vol. 536).

Research output: Chapter or Contribution to Book › Literary contribution

Cho, S, May, G, Tourkogiorgis, I, Perez, R, Lazaro, O, de la Maza, B & Kiritsis, D 2018, A hybrid machine learning approach for predictive maintenance in smart factories of the future. in G von Cieminski, D Kiritsis, I Moon, J Park & GM Lee (eds), Advances in Production Management Systems. Smart Manufacturing for Industry 4.0 - IFIP WG 5.7 International Conference, APMS 2018, Proceedings. IFIP Advances in Information and Communication Technology, vol. 536, pp. 311-317, IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2018, Seoul, Korea, Republic of, 8/26/18. https://doi.org/10.1007/978-3-319-99707-0_39

Cho S, May G, Tourkogiorgis I, Perez R, Lazaro O, de la Maza B et al. A hybrid machine learning approach for predictive maintenance in smart factories of the future. In von Cieminski G, Kiritsis D, Moon I, Park J, Lee GM, editors, Advances in Production Management Systems. Smart Manufacturing for Industry 4.0 - IFIP WG 5.7 International Conference, APMS 2018, Proceedings. 2018. p. 311-317. (IFIP Advances in Information and Communication Technology). doi: 10.1007/978-3-319-99707-0_39

Cho, Sangje ; May, Gökan ; Tourkogiorgis, Ioannis et al. / A hybrid machine learning approach for predictive maintenance in smart factories of the future. Advances in Production Management Systems. Smart Manufacturing for Industry 4.0 - IFIP WG 5.7 International Conference, APMS 2018, Proceedings. editor / Gregor von Cieminski ; Dimitris Kiritsis ; Ilkyeong Moon ; Jinwoo Park ; Gyu M. Lee. 2018. pp. 311-317 (IFIP Advances in Information and Communication Technology).

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A hybrid machine learning approach for predictive maintenance in smart factories of the future

Publication series

Conference

ASJC Scopus Subject Areas

Keywords

Access to Document

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