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Improve predictive maintenance through the application of artificial intelligence: A systematic review
  • Anthony Scaife D
Anthony Scaife D
University of Maryland Global Campus Library

Corresponding Author:[email protected]

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Abstract

Facility operations and maintenance are defined as the functions, duties, and labor required daily to operate and preserve a facility asset to ensure its original function is available for its primary use and its operations are maintained throughout the facility's life. Organizations, facility management professionals, and their stakeholders expend billions of dollars annually to perform this function in the United States. Much of the cost is on inadequate facility operations that may be avoided. This rapid evidence assessment used the theoretical lens of the adaptive structuration theory and reviewed the current body of scholarly literature to identify how artificial intelligence is used with predictive maintenance to reduce a facility operations program's operations and maintenance costs. Through an organized systematic review process, this research shall utilize peer-reviewed scholarly articles published within the last five years to perform a rapid evidence assessment of predictive maintenance and artificial intelligence in facility operations. Through this rapid evidence assessment, the research finds three common themes that respond to the research question. The most significant theme is artificial intelligence, once implemented in the process, provides unbiased investment and repair recommendations from the analyzed data. An unanticipated discovery of interest is that the current body of literature identifies insufficient data as the number one barrier to the full implementation of artificial intelligence within a facility operations program.