04267nam a22005175i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001600153072001500169072002300184072001400207245016700221250001800388264006900406300006700475336002600542337002600568338003600594347002400630490005600654505056900710520165901279650002402938650004402962650002903006650002803035650002803063650002403091650002803115650002903143650004303172700007403215700007503289700007503364700007603439710003403515773002603549776003603575776003603611830005603647856004603703978-3-031-39619-9DE-He21320251030110904.0cr nn 008mamaa231130s2024    sz |    s    |||| 0|eng d  a97830313961997 a10.1007/978-3-031-39619-92doi 4aTK5105.8857 7aUT2bicssc 7aCOM0430002bisacsh 7aUT2thema10aInternational Congress and Workshop on Industrial AI and eMaintenance 2023h[electronic resource] /cedited by Uday Kumar, Ramin Karim, Diego Galar, Ravdeep Kour.  a1st ed. 2024. 1aCham :bSpringer Nature Switzerland :bImprint: Springer,c2024.  aXII, 801 p. 351 illus., 287 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aLecture Notes in Mechanical Engineering,x2195-43640 aUse cases of Generative AI in Asset Management of Railways -- A neuroergonomics mirror-based platform to enhance cognitive impairments in fighter pilots -- Risk-based safety improvements in railway asset management -- Performance of Reinforcement Learning in Molecular Dynamics Simulations: A Case Study of Hydrocarbon Dynamics -- Causal Effects of Railway Track Maintenance – An Experimental Case Study of Tamping -- Self-Driving Cars in the Arctic Environment -- Towards a Railway Infrastructure Digital Twin Framework for African Railway Lifecycle Management.  aThis proceedings brings together the papers presented at the International Congress and Workshop on Industrial AI and eMaintenance 2023 (IAI2023). The conference integrates the themes and topics of three conferences: Industrial AI & eMaintenance, Condition Monitoring and Diagnostic Engineering Management (COMADEM) and, Advances in Reliability, Maintainability and Supportability (ARMS) on a single platform. This proceedings serves both academy and industry in providing an excellent platform for collaboration by providing a forum for exchange of ideas and networking. The 21st century has seen remarkable progress in Artificial Intelligence, with application to a variety of fields (computer vision, automatic translation, sentiment analysis in social networks, robotics, etc.) The IAI2023 focuses on Industrial Artificial Intelligence, or IAI. The emergence of industrial AI applications holds tremendous promises in terms of achieving excellence and cost-effectiveness in the operation and maintenance of industrial assets. Opportunities in Industrial AI exist in many industries such as aerospace, railways, mining, construction, process industry, etc. Its development is powered by several trends: the Internet of Things (IoT); the increasing convergence between OT (operational technologies) and IT (information technologies); last but not least, the unabated fast-paced developments of advanced analytics. However, numerous technical and organizational challenges to the widespread development of industrial AI still exist. The IAI2023 conference and its proceedings foster fruitful discussions between AI creators and industrial practitioners. 0aInternet of things. 0aCooperating objects (Computer systems). 0aArtificial intelligence. 0aIndustrial engineering. 0aProduction engineering.14aInternet of Things.24aCyber-Physical Systems.24aArtificial Intelligence.24aIndustrial and Production Engineering.1 aKumar, Uday.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt1 aKarim, Ramin.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt1 aGalar, Diego.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt1 aKour, Ravdeep.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303139618208iPrinted edition:z9783031396205 0aLecture Notes in Mechanical Engineering,x2195-436440uhttps://doi.org/10.1007/978-3-031-39619-9