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Evolving From Predictive to Liquid Maintenance in Postmodern Industry

Authors :
Manuel Lozano Rodriguez
Carlos E. Torres
Source :
Encyclopedia of Data Science and Machine Learning ISBN: 9781799892205
Publication Year :
2022
Publisher :
IGI Global, 2022.

Abstract

PdM is unready to face the near-future incoming challenges since it is anchored in an obsolete paradigm alien to the incoming cyber-physical reality and unfit for unbelievable data density. In addition to this, PdM is wormed by philosophical hiddenness around time and taxonomies abuse; it is not the sound subdiscipline it appears to be. So, we are doomed to dialogue and get along with AIs if we want to break our human predictiveness ceiling glass and keep PdM improving. In this article, the authors explain not only the turn of the tide but how to flow towards a non-essentialist PdM paradigm.

Details

ISBN :
978-1-79989-220-5
ISBNs :
9781799892205
Database :
OpenAIRE
Journal :
Encyclopedia of Data Science and Machine Learning ISBN: 9781799892205
Accession number :
edsair.doi...........1704a922d0ec57154db039a94539ac20
Full Text :
https://doi.org/10.4018/978-1-7998-9220-5.ch130