A Review of data-driven decision-making methods for Industry 4.0. Maintenance applications

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      <subfield code="c">Alexandros Bousdekis... [et al.]</subfield>
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      <subfield code="a"> The current paper reviews the literature on data-driven decision- making in maintenance and outlines directions for future research towards data-driven decision-making for Industry 4.0 maintenance applications. The main research directions include the coupling of decision-making with augmented reality for seamless interfacing that combines the real and virtual worlds of manufacturing operators; methods and techniques for addressing uncertainty of data, in lieu of emerging Internet of Things (IoT) devices; integration of maintenance decision-making with other operations such as scheduling and planning; utilization of the cloud continuum for optimal deployment of decision-making services; capability of decision-making methods to cope with big data; incorporation of advanced security mechanisms; and coupling decision-making with simulation software, autonomous robots, and other additive manufacturing initiatives</subfield>
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      <subfield code="t">Electronics.- Basel, Switzerland : MDPI, A.G.</subfield>
      <subfield code="g">Vol. 10, nº 828, 31 March 2021 ; 20 p.</subfield>
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