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Intelligent prognostics tools and e-maintenance

delete2006-08-01
delete431
PRE
AI
J
Jay Lee *
倪
倪军 (Jun Ni)
D
Dragan Djurdjanović
H
Hai Qiu
H
Haitao Liao
DOI:10.1016/j.compind.2006.02.014delete
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Abstract

Abstract

En 中文
In today's global competitive marketplace, there is intense pressure for manufacturing industries to continuously reduce and eliminate costly, unscheduled downtime and unexpected breakdowns. With the advent of Internet and tether-free technologies, companies necessitate dramatic changes in transforming traditional fail and fix (FAF) maintenance practices to a predict and prevent (PAP) e-maintenance methodology. E-maintenance addresses the fundamental needs of predictive intelligence tools to monitor the degradation rather than detecting the faults in a networked environment and, ultimately to optimize asset utilization in the facility. This paper introduces the emerging field of e-maintenance and its critical elements. Furthermore, performance assessment and prediction tools are introduced for continuous assessment and prediction of a particular product's performance, ultimately enable proactive maintenance to prevent machine from breakdowns. Recent advances on intelligent prognostic technologies and tools are discussed. Several case studies are introduced to validate these developed technologies and tools. (C) 2006 Elsevier B.V. All rights reserved.
Keywords:
e-maintenance
prognostics
predictive maintenance
remote monitoring
AI Summary

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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Computers in Industry cover
Computers in Industry
IF:
9.1
Papers:
2.9K
Citations:
1.1W

Organization

No organization information available
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