Intelligent prognostics tools and e-maintenance

Jay Lee, Jun Ni, Dragan Djurdjanovic, Hai Qiu, Haitao Liao

Research output: Contribution to journalArticle

387 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)476-489
Number of pages14
JournalComputers in Industry
Volume57
Issue number6
DOIs
StatePublished - Aug 2006
Externally publishedYes

Fingerprint

Industry
Internet
Degradation
Breakdown
Prediction
Performance assessment
Fault
Manufacturing industries
Methodology
Assets
World Wide Web

Keywords

  • E-maintenance
  • Predictive maintenance
  • Prognostics
  • Remote monitoring

ASJC Scopus subject areas

  • Computer Science Applications
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

Cite this

Intelligent prognostics tools and e-maintenance. / Lee, Jay; Ni, Jun; Djurdjanovic, Dragan; Qiu, Hai; Liao, Haitao.

In: Computers in Industry, Vol. 57, No. 6, 08.2006, p. 476-489.

Research output: Contribution to journalArticle

Lee, Jay ; Ni, Jun ; Djurdjanovic, Dragan ; Qiu, Hai ; Liao, Haitao. / Intelligent prognostics tools and e-maintenance. In: Computers in Industry. 2006 ; Vol. 57, No. 6. pp. 476-489.
@article{dcdd1f1971c14b0992b994d7a37a90b1,
title = "Intelligent prognostics tools and e-maintenance",
abstract = "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.",
keywords = "E-maintenance, Predictive maintenance, Prognostics, Remote monitoring",
author = "Jay Lee and Jun Ni and Dragan Djurdjanovic and Hai Qiu and Haitao Liao",
year = "2006",
month = "8",
doi = "10.1016/j.compind.2006.02.014",
language = "English (US)",
volume = "57",
pages = "476--489",
journal = "Computers in Industry",
issn = "0166-3615",
publisher = "Elsevier",
number = "6",

}

TY - JOUR

T1 - Intelligent prognostics tools and e-maintenance

AU - Lee, Jay

AU - Ni, Jun

AU - Djurdjanovic, Dragan

AU - Qiu, Hai

AU - Liao, Haitao

PY - 2006/8

Y1 - 2006/8

N2 - 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.

AB - 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.

KW - E-maintenance

KW - Predictive maintenance

KW - Prognostics

KW - Remote monitoring

UR - http://www.scopus.com/inward/record.url?scp=33746216902&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33746216902&partnerID=8YFLogxK

U2 - 10.1016/j.compind.2006.02.014

DO - 10.1016/j.compind.2006.02.014

M3 - Article

AN - SCOPUS:33746216902

VL - 57

SP - 476

EP - 489

JO - Computers in Industry

JF - Computers in Industry

SN - 0166-3615

IS - 6

ER -