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| 02048nam 2200337zi 4500 |
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| 001 | 9.860651 |
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| 003 | CaOODSP |
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| 005 | 20221107160542 |
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| 006 | m o d f |
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| 007 | cr ||||||||||| |
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| 008 | 180816e201808##onca o f000 0 eng d |
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| 020 | |a9780660275987|z9780660273051 |
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| 040 | |aCaOODSP|beng|erda|cCaOODSP |
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| 043 | |an-cn--- |
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| 086 | 1 |aNR16-244/2018E-PDF|zNR16-237/2018E-PDF |
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| 245 | 00|aIntelligent maintenance systems for platforms. |
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| 264 | 1|a[Ottawa] : |bNational Research Council Canada = Conseil national de recherches Canada, |cAugust 2018. |
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| 300 | |a1 online resource (2 unnumbered pages) : |billustrations |
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| 336 | |atext|btxt|2rdacontent |
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| 337 | |acomputer|bc|2rdamedia |
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| 338 | |aonline resource|bcr|2rdacarrier |
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| 500 | |aTitle from caption. |
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| 500 | |aIncorrect catalogue number (NR16-237/2018E-PDF) and ISBN (9780660273051) printed in this publication. |
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| 500 | |aIssued also in French under title: Systèmes de maintenance intelligents pour les plateformes. |
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| 520 | |a"Intelligent Maintenance Systems (IMS), or advanced Condition-Based Maintenance (CBM) systems, are predictive technologies that integrate diagnostic and/or prognostic tools to facilitate decision-making. This “smart” approach to identifying, scheduling and performing maintenance tasks is based on a holistic real-time understanding of a platform’s critical components. Accumulation of historical and current data from sensors provide a continuous dynamic flow of information throughout the maintenance process with the goal of tracking health degradation to predict which components are likely to fail, and when"--Page [1]. |
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| 692 | 07|2gccst|aMaintenance |
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| 692 | 07|2gccst|aIntelligent systems |
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| 692 | 07|2gccst|aTechnological innovation |
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| 710 | 2 |aNational Research Council Canada. |
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| 775 | 08|tSystèmes de maintenance intelligents pour les plateformes.|w(CaOODSP)9.860652 |
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| 856 | 40|qPDF|s169 KB|uhttps://publications.gc.ca/collections/collection_2019/cnrc-nrc/NR16-244-2018-eng.pdf |
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