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020 _a9783031714955
_9978-3-031-71495-5
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082 0 4 _a670
_223
245 1 0 _aArtificial Intelligence for Safety and Reliability Engineering
_h[electronic resource] :
_bMethods, Applications, and Challenges /
_cedited by Kim Phuc Tran.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aV, 199 p. 56 illus., 48 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Series in Reliability Engineering,
_x2196-999X
505 0 _aIntroduction to Artificial Intelligence for Safety and Reliability Engineering -- Artificial Intelligence for Safety and Reliability Engineering in Industry 5.0 Methods, Applications and Challenges -- System Reliability Inference for Common Cause Failure Model in Contexts of Missing Information -- Predictive maintenance enabled by a Light Weight Federated Learning in Smart Manufacturing: Remaining Useful Lifetime Prediction -- Explainable Trustworthy and Transparent Artificial Intelligence for Reliability Engineering and Safety Applications -- Inverse Reinforcement Learning for Predictive Maintenance -- Reliability and Risk Assessment with Explainable Artificial Intelligence -- An Anomaly Detection Framework for Safety and Reliability Engineering -- Wearable Technology for Workplace Safety with Embedded Artificial Intelligence -- Safety and Reliability of Artificial Intelligence systems -- Physics-informed machine learning for reliability and systems safety applications.
520 _aThis book is a comprehensive exploration of the latest theoretical research, technological advancements, and real-world applications of artificial intelligence (AI) for safety and reliability engineering. Smart manufacturing relies on predictive maintenance (PdM) to ensure sustainable production systems, and the integration of AI has become increasingly prevalent in this field. This book serves as a valuable resource for researchers, practitioners, and decision-makers in manufacturing. By combining theoretical research, practical applications, and case studies, it equips readers with the necessary knowledge and tools to implement AI for safety and reliability engineering effectively in smart manufacturing contexts. .
541 _fUABC ;
_cPerpetuidad
650 0 _aIndustrial engineering.
650 0 _aProduction engineering.
650 0 _aArtificial intelligence.
650 0 _aProduction management.
650 1 4 _aIndustrial and Production Engineering.
650 2 4 _aArtificial Intelligence.
650 2 4 _aProduction.
700 1 _aTran, Kim Phuc.
_eeditor.
_0(orcid)0000-0002-6005-1497
_1https://orcid.org/0000-0002-6005-1497
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031714948
776 0 8 _iPrinted edition:
_z9783031714962
776 0 8 _iPrinted edition:
_z9783031714979
830 0 _aSpringer Series in Reliability Engineering,
_x2196-999X
856 4 0 _zLibro electrónico
_uhttp://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-3-031-71495-5
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cLIBRO_ELEC
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