A review of diagnostic and prognostic capabilities and best practices for manufacturing.

J Intell Manuf

Engineering Laboratory, National Institute of Standards and Technology (NIST), 100 Bureau Drive, Gaithersburg, MD 20899-8220, USA.

Published: January 2019

AI Article Synopsis

  • PHM technologies enhance maintenance efficiency and cut costs by utilizing real-time and historical data for diagnostics and prognostics.
  • They provide actionable insights that improve performance, safety, and reliability in manufacturing systems.
  • The field is still developing, with a need for innovative solutions and best practices to address current challenges and meet future demands.

Article Abstract

Prognostics and health management (PHM) technologies reduce time and costs for maintenance of products or processes through efficient and cost-effective diagnostic and prognostic activities. PHM systems use real-time and historical state information of subsystems and components to provide actionable information, enabling intelligent decision-making for improved performance, safety, reliability, and maintainability. However, PHM is still an emerging field, and much of the published work has been either too exploratory or too limited in scope. Future smart manufacturing systems will require PHM capabilities that overcome current challenges, while meeting future needs based on best practices, for implementation of diagnostics and prognostics. This paper reviews the challenges, needs, methods, and best practices for PHM within manufacturing systems. This includes PHM system development of numerous areas highlighted by diagnostics, prognostics, dependability analysis, data management, and business. Based on current capabilities, PHM systems are shown to benefit from open-system architectures, cost-benefit analyses, method verification and validation, and standards.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6391061PMC
http://dx.doi.org/10.1007/s10845-016-1228-8DOI Listing

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