Loading…

A Generic Prognostic Methodology Using Damage Trajectory Models

In modern industries, there is intense pressure to continuously reduce costly, unscheduled maintenance of complex systems. To obtain high availability with reduced life cycle total ownership costs, classical maintenance policies are not optimal. Indeed, these polices do not allow us to perform maint...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on reliability 2009-06, Vol.58 (2), p.277-285
Main Authors: Peysson, F., Ouladsine, M., Outbib, R., Leger, J.-B., Myx, O., Allemand, C.
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c352t-c0473622db7abddd7d5f683dad2daf3995c35054de821e92efb22f0ae8512d603
cites cdi_FETCH-LOGICAL-c352t-c0473622db7abddd7d5f683dad2daf3995c35054de821e92efb22f0ae8512d603
container_end_page 285
container_issue 2
container_start_page 277
container_title IEEE transactions on reliability
container_volume 58
creator Peysson, F.
Ouladsine, M.
Outbib, R.
Leger, J.-B.
Myx, O.
Allemand, C.
description In modern industries, there is intense pressure to continuously reduce costly, unscheduled maintenance of complex systems. To obtain high availability with reduced life cycle total ownership costs, classical maintenance policies are not optimal. Indeed, these polices do not allow us to perform maintenance only when it is necessary because they are not able to forecast system damage states in the future. To predict precisely the future system damage state, it is necessary to take into account how and where the system will be used. To build incremental damage models, this paper presents a generic methodology and formalism based on the system decomposition in three levels: environment, mission, and process. Predictions are performed via a sequence of known mission parameters, and environmental conditions. This allows for mission and maintenance planning by taking into account the predicted system damages over time.
doi_str_mv 10.1109/TR.2009.2020123
format article
fullrecord <record><control><sourceid>proquest_ieee_</sourceid><recordid>TN_cdi_proquest_miscellaneous_36343650</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>4967919</ieee_id><sourcerecordid>1365134410</sourcerecordid><originalsourceid>FETCH-LOGICAL-c352t-c0473622db7abddd7d5f683dad2daf3995c35054de821e92efb22f0ae8512d603</originalsourceid><addsrcrecordid>eNp90D1PwzAQBmALgUQpzAwsEQNiSevPJJ5QVaAgtQJV6Wy58SWkSuNip0P_PY5aMTCw-HzScyfdi9AtwSNCsBznyxHFWIaHYkLZGRoQIbKYpJScowHGJIuloPISXXm_CS3nMhugp0k0gxZcXUSfzlat9V34LqD7ssY2tjpEK1-3VfSst7qCKHd6A0Vn3SFaWAONv0YXpW483JzqEK1eX_LpWzz_mL1PJ_O4YIJ2cYF5yhJKzTrVa2NMakSZZMxoQ40umZQiOCy4gYwSkBTKNaUl1pAJQk2C2RA9HPfunP3eg-_UtvYFNI1uwe69YgnjLBE9fPwXkqAI45z09P4P3di9a8MZKhOJJFQwGdD4iApnvXdQqp2rt9odFMGqD17lS9UHr07Bh4m740QNAL-ayySVRLIfuX59Dg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>856912539</pqid></control><display><type>article</type><title>A Generic Prognostic Methodology Using Damage Trajectory Models</title><source>IEEE Xplore (Online service)</source><creator>Peysson, F. ; Ouladsine, M. ; Outbib, R. ; Leger, J.-B. ; Myx, O. ; Allemand, C.</creator><creatorcontrib>Peysson, F. ; Ouladsine, M. ; Outbib, R. ; Leger, J.-B. ; Myx, O. ; Allemand, C.</creatorcontrib><description>In modern industries, there is intense pressure to continuously reduce costly, unscheduled maintenance of complex systems. To obtain high availability with reduced life cycle total ownership costs, classical maintenance policies are not optimal. Indeed, these polices do not allow us to perform maintenance only when it is necessary because they are not able to forecast system damage states in the future. To predict precisely the future system damage state, it is necessary to take into account how and where the system will be used. To build incremental damage models, this paper presents a generic methodology and formalism based on the system decomposition in three levels: environment, mission, and process. Predictions are performed via a sequence of known mission parameters, and environmental conditions. This allows for mission and maintenance planning by taking into account the predicted system damages over time.</description><identifier>ISSN: 0018-9529</identifier><identifier>EISSN: 1558-1721</identifier><identifier>DOI: 10.1109/TR.2009.2020123</identifier><identifier>CODEN: IERQAD</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Accelerated lifetime ; Acceleration ; Availability ; Complex systems ; condition based maintenance ; Construction ; Context modeling ; Cost function ; Damage ; Hazards ; Job shop scheduling ; Laboratories ; Large scale integration ; Maintenance ; Mathematical models ; Methodology ; Missions ; Policies ; Prognostics and health management ; Systems engineering and theory</subject><ispartof>IEEE transactions on reliability, 2009-06, Vol.58 (2), p.277-285</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2009</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c352t-c0473622db7abddd7d5f683dad2daf3995c35054de821e92efb22f0ae8512d603</citedby><cites>FETCH-LOGICAL-c352t-c0473622db7abddd7d5f683dad2daf3995c35054de821e92efb22f0ae8512d603</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4967919$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,777,781,27906,27907,54778</link.rule.ids></links><search><creatorcontrib>Peysson, F.</creatorcontrib><creatorcontrib>Ouladsine, M.</creatorcontrib><creatorcontrib>Outbib, R.</creatorcontrib><creatorcontrib>Leger, J.-B.</creatorcontrib><creatorcontrib>Myx, O.</creatorcontrib><creatorcontrib>Allemand, C.</creatorcontrib><title>A Generic Prognostic Methodology Using Damage Trajectory Models</title><title>IEEE transactions on reliability</title><addtitle>TR</addtitle><description>In modern industries, there is intense pressure to continuously reduce costly, unscheduled maintenance of complex systems. To obtain high availability with reduced life cycle total ownership costs, classical maintenance policies are not optimal. Indeed, these polices do not allow us to perform maintenance only when it is necessary because they are not able to forecast system damage states in the future. To predict precisely the future system damage state, it is necessary to take into account how and where the system will be used. To build incremental damage models, this paper presents a generic methodology and formalism based on the system decomposition in three levels: environment, mission, and process. Predictions are performed via a sequence of known mission parameters, and environmental conditions. This allows for mission and maintenance planning by taking into account the predicted system damages over time.</description><subject>Accelerated lifetime</subject><subject>Acceleration</subject><subject>Availability</subject><subject>Complex systems</subject><subject>condition based maintenance</subject><subject>Construction</subject><subject>Context modeling</subject><subject>Cost function</subject><subject>Damage</subject><subject>Hazards</subject><subject>Job shop scheduling</subject><subject>Laboratories</subject><subject>Large scale integration</subject><subject>Maintenance</subject><subject>Mathematical models</subject><subject>Methodology</subject><subject>Missions</subject><subject>Policies</subject><subject>Prognostics and health management</subject><subject>Systems engineering and theory</subject><issn>0018-9529</issn><issn>1558-1721</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><recordid>eNp90D1PwzAQBmALgUQpzAwsEQNiSevPJJ5QVaAgtQJV6Wy58SWkSuNip0P_PY5aMTCw-HzScyfdi9AtwSNCsBznyxHFWIaHYkLZGRoQIbKYpJScowHGJIuloPISXXm_CS3nMhugp0k0gxZcXUSfzlat9V34LqD7ssY2tjpEK1-3VfSst7qCKHd6A0Vn3SFaWAONv0YXpW483JzqEK1eX_LpWzz_mL1PJ_O4YIJ2cYF5yhJKzTrVa2NMakSZZMxoQ40umZQiOCy4gYwSkBTKNaUl1pAJQk2C2RA9HPfunP3eg-_UtvYFNI1uwe69YgnjLBE9fPwXkqAI45z09P4P3di9a8MZKhOJJFQwGdD4iApnvXdQqp2rt9odFMGqD17lS9UHr07Bh4m740QNAL-ayySVRLIfuX59Dg</recordid><startdate>20090601</startdate><enddate>20090601</enddate><creator>Peysson, F.</creator><creator>Ouladsine, M.</creator><creator>Outbib, R.</creator><creator>Leger, J.-B.</creator><creator>Myx, O.</creator><creator>Allemand, C.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope><scope>F28</scope><scope>FR3</scope></search><sort><creationdate>20090601</creationdate><title>A Generic Prognostic Methodology Using Damage Trajectory Models</title><author>Peysson, F. ; Ouladsine, M. ; Outbib, R. ; Leger, J.-B. ; Myx, O. ; Allemand, C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c352t-c0473622db7abddd7d5f683dad2daf3995c35054de821e92efb22f0ae8512d603</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Accelerated lifetime</topic><topic>Acceleration</topic><topic>Availability</topic><topic>Complex systems</topic><topic>condition based maintenance</topic><topic>Construction</topic><topic>Context modeling</topic><topic>Cost function</topic><topic>Damage</topic><topic>Hazards</topic><topic>Job shop scheduling</topic><topic>Laboratories</topic><topic>Large scale integration</topic><topic>Maintenance</topic><topic>Mathematical models</topic><topic>Methodology</topic><topic>Missions</topic><topic>Policies</topic><topic>Prognostics and health management</topic><topic>Systems engineering and theory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Peysson, F.</creatorcontrib><creatorcontrib>Ouladsine, M.</creatorcontrib><creatorcontrib>Outbib, R.</creatorcontrib><creatorcontrib>Leger, J.-B.</creatorcontrib><creatorcontrib>Myx, O.</creatorcontrib><creatorcontrib>Allemand, C.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998–Present</collection><collection>IEEE</collection><collection>CrossRef</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE transactions on reliability</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Peysson, F.</au><au>Ouladsine, M.</au><au>Outbib, R.</au><au>Leger, J.-B.</au><au>Myx, O.</au><au>Allemand, C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Generic Prognostic Methodology Using Damage Trajectory Models</atitle><jtitle>IEEE transactions on reliability</jtitle><stitle>TR</stitle><date>2009-06-01</date><risdate>2009</risdate><volume>58</volume><issue>2</issue><spage>277</spage><epage>285</epage><pages>277-285</pages><issn>0018-9529</issn><eissn>1558-1721</eissn><coden>IERQAD</coden><abstract>In modern industries, there is intense pressure to continuously reduce costly, unscheduled maintenance of complex systems. To obtain high availability with reduced life cycle total ownership costs, classical maintenance policies are not optimal. Indeed, these polices do not allow us to perform maintenance only when it is necessary because they are not able to forecast system damage states in the future. To predict precisely the future system damage state, it is necessary to take into account how and where the system will be used. To build incremental damage models, this paper presents a generic methodology and formalism based on the system decomposition in three levels: environment, mission, and process. Predictions are performed via a sequence of known mission parameters, and environmental conditions. This allows for mission and maintenance planning by taking into account the predicted system damages over time.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TR.2009.2020123</doi><tpages>9</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0018-9529
ispartof IEEE transactions on reliability, 2009-06, Vol.58 (2), p.277-285
issn 0018-9529
1558-1721
language eng
recordid cdi_proquest_miscellaneous_36343650
source IEEE Xplore (Online service)
subjects Accelerated lifetime
Acceleration
Availability
Complex systems
condition based maintenance
Construction
Context modeling
Cost function
Damage
Hazards
Job shop scheduling
Laboratories
Large scale integration
Maintenance
Mathematical models
Methodology
Missions
Policies
Prognostics and health management
Systems engineering and theory
title A Generic Prognostic Methodology Using Damage Trajectory Models
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-17T07%3A57%3A26IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_ieee_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20Generic%20Prognostic%20Methodology%20Using%20Damage%20Trajectory%20Models&rft.jtitle=IEEE%20transactions%20on%20reliability&rft.au=Peysson,%20F.&rft.date=2009-06-01&rft.volume=58&rft.issue=2&rft.spage=277&rft.epage=285&rft.pages=277-285&rft.issn=0018-9529&rft.eissn=1558-1721&rft.coden=IERQAD&rft_id=info:doi/10.1109/TR.2009.2020123&rft_dat=%3Cproquest_ieee_%3E1365134410%3C/proquest_ieee_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c352t-c0473622db7abddd7d5f683dad2daf3995c35054de821e92efb22f0ae8512d603%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=856912539&rft_id=info:pmid/&rft_ieee_id=4967919&rfr_iscdi=true