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020 _a9781394275045
020 _a9781394275076
_qelectronic book
020 _a1394275072
_qelectronic book
020 _z9781394275045
_qhardcover
035 _a(OCoLC)1523157047
035 9 _a(OCLCCM-CC)1523157047
037 _a9781394275045
_bO'Reilly Media
040 _aYDX
_beng
_cYDX
_dORMDA
_dOCLCO
_dDG1
_dCLOUD
041 _aeng
049 _aMAIN
050 4 _aQ335
245 0 0 _aArtificial intelligence and machine learning for industry 4.0 /
_cedited by M. Thirunavukkarasan... [and 4 others].
264 1 _aHoboken, NJ :
_bJohn WIley & Sons, Inc. ;
_aBeverly, MA :
_bScrivener Publishing LLC,
_c2025.
264 4 _c©2025
300 _a1 online resource
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
500 _aIncludes index.
520 _aThis book is essential for any leader seeking to understand how to leverage intelligent automation and predictive maintenance to drive innovation, enhance productivity, and minimize downtime in their manufacturing processes. Intelligent automation is widely considered to have the greatest potential for Industry 4.0 innovations for corporations. Industrial machinery is increasingly being upgraded to intelligent machines that can perceive, act, evolve, and interact in an industrial environment. The innovative technologies featured in this machinery include the Internet of Things, cyber-physical systems, and artificial intelligence. Artificial intelligence enables computer systems to learn from experience, adapt to new input data, and perform intelligent tasks. The significance of AI is not found in its computational models, but in how humans can use them. Consistently observing equipment to keep it from malfunctioning is the procedure of predictive maintenance. Predictive maintenance includes a periodic maintenance schedule and anticipates equipment failure rather than responding to equipment problems. Currently, the industry is struggling to adopt a viable and trustworthy predictive maintenance plan for machinery. The goal of predictive maintenance is to reduce the amount of unanticipated downtime that a machine experiences due to a failure in a highly automated manufacturing line. In recent years, manufacturing across the globe has increasingly embraced the Industry 4.0 concept. Greater solutions than those offered by conventional maintenance are promised by machine learning, revealing precisely how AI and machine learning-based models are growing more prevalent in numerous industries for intelligent performance and greater productivity. This book emphasizes technological developments that could have great influence on an industrial revolution and introduces the fundamental technologies responsible for directing the development of innovative firms. Decision-making requires a vast intake of data and customization in the manufacturing process, which managers and machines both deal with on a regular basis. One of the biggest issues in this field is the capacity to foresee when maintenance of assets is necessary. Leaders in the sector will have to make careful decisions about how, when, and where to employ these technologies. Artificial Intelligence and Machine Learning for Industry 4.0offers contemporary technological advancements in AI and machine learning from an Industry 4.0 perspective, looking at their prospects, obstacles, and potential applications.
650 0 _aArtificial intelligence.
_0http://id.loc.gov/authorities/subjects/sh85008180
650 0 _aMachine learning.
_0http://id.loc.gov/authorities/subjects/sh85079324
650 6 _aIntelligence artificielle.
650 6 _aApprentissage automatique.
650 7 _aartificial intelligence.
_2aat
650 7 _aIntelligence (AI) & Semantics.
_2bisacsh/2024
650 7 _aCOMPUTERS.
_2bisacsh/2024
655 0 _aElectronic books.
700 1 _aThirunavukkarasan, M.,
_eeditor.
856 4 0 _uhttps://onlinelibrary.wiley.com/doi/book/10.1002/9781394275076
_yFull text is available at Wiley Online Library. Click here to view.
942 _2ddc
_cER