A hierarchical decision-making framework for the assessment of the prediction capability of prognostic methods
Identifieur interne : 000026 ( Main/Exploration ); précédent : 000025; suivant : 000027A hierarchical decision-making framework for the assessment of the prediction capability of prognostic methods
Auteurs : Zhiguo Zeng [France] ; Francesco Di Maio [Italie] ; Enrico Zio [France] ; Rui Kang [États-Unis]Source :
- Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability [ 1748-006X ] ; 2017-02-15.
Abstract
8 In Prognostics and Health Management (PHM), the prediction capability of a prognostic method refers to its 9 ability to provide trustable predictions of the Remaining Useful Life (RUL), with the quality characteristics 10 required by the related maintenance decision making. The prediction capability heavily influences the decision 11 maker's attitude towards taking the risk of using the predicted RUL to inform the maintenance decisions. In this 12 paper, a four-layer, top-down, hierarchical decision making framework is proposed to assess the prediction 13 capability of prognostic methods. In the framework, prediction capability is broken down into two criteria (Layer 2), 14 six sub-criteria (Layer 3) and 19 basic sub-criteria (Layer 4). Based on the hierarchical framework, a bottom-up, 15 quantitative approach is developed for the assessment of the prediction capability, using the information and data 16 collected at the Layer-4 basic sub-criteria level. Analytical Hierarchical Process (AHP) is applied for the evaluation 17 and aggregation of the sub-criteria and Support Vector Machine (SVM) is applied to develop a classification-based 18 approach for prediction capability assessment. The framework and quantitative approach are applied on a simulated 19 case study to assess the prediction capabilities of three prognostic methods of literature: fuzzy similarity, 20 feed-forward neural network and hidden semi-Markov model. The results show the feasibility of the practical 21 application of the framework and its quantitative assessment approach, and that the assessed prediction capability 22 can be used to support the selection of the suitable prognostic method for a given application.
Url:
DOI: 10.1177/1748006X16683321
Affiliations:
Links toward previous steps (curation, corpus...)
- to stream Hal, to step Corpus: 000041
- to stream Hal, to step Curation: 000041
- to stream Hal, to step Checkpoint: 000026
- to stream Main, to step Merge: 000026
- to stream Main, to step Curation: 000026
Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">A hierarchical decision-making framework for the assessment of the prediction capability of prognostic methods</title><author><name sortKey="Zeng, Zhiguo" sort="Zeng, Zhiguo" uniqKey="Zeng Z" first="Zhiguo" last="Zeng">Zhiguo Zeng</name><affiliation wicri:level="1"><hal:affiliation type="laboratory" xml:id="struct-11769" status="VALID"><idno type="RNSR">199814131Y</idno><orgName>Laboratoire Génie Industriel - EA 2606</orgName><orgName type="acronym">LGI</orgName><desc><address><addrLine>CentraleSupélec - Grande Voie des Vignes - 92295 Chatenay-Malabry</addrLine><country key="FR"></country></address><ref type="url">http://www.lgi.ecp.fr</ref></desc><listRelation><relation active="#struct-411575" type="direct"></relation></listRelation><tutelles><tutelle active="#struct-411575" type="direct"><org type="institution" xml:id="struct-411575" status="VALID"><orgName>CentraleSupélec</orgName><desc><address><addrLine>3, rue Joliot Curie,Plateau de Moulon,91192 GIF-SUR-YVETTE Cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.centralesupelec.fr</ref></desc></org></tutelle></tutelles></hal:affiliation><country>France</country></affiliation></author><author><name sortKey="Di Maio, Francesco" sort="Di Maio, Francesco" uniqKey="Di Maio F" first="Francesco" last="Di Maio">Francesco Di Maio</name><affiliation wicri:level="1"><hal:affiliation type="laboratory" xml:id="struct-161209" status="INCOMING"><orgName>Dipartimento di Energia</orgName><desc><address><country key="IT"></country></address></desc><listRelation><relation active="#struct-125443" type="direct"></relation></listRelation><tutelles><tutelle active="#struct-125443" type="direct"><org type="institution" xml:id="struct-125443" status="VALID"><orgName>Politecnico di Milano [Milan]</orgName><desc><address><addrLine>Piazza Leonardo da Vinci, 32 20133 Milano</addrLine><country key="IT"></country></address><ref type="url">http://www.polimi.it/</ref></desc></org></tutelle></tutelles></hal:affiliation><country>Italie</country></affiliation></author><author><name sortKey="Zio, Enrico" sort="Zio, Enrico" uniqKey="Zio E" first="Enrico" last="Zio">Enrico Zio</name><affiliation wicri:level="1"><hal:affiliation type="researchteam" xml:id="struct-391008" status="INCOMING"><orgName>Chaire Sciences des Systèmes et Défis Energétiques EDF/ECP/Supélec</orgName><desc><address><country key="FR"></country></address></desc><listRelation><relation active="#struct-11769" type="direct"></relation><relation active="#struct-411575" type="indirect"></relation><relation active="#struct-161195" type="direct"></relation><relation active="#struct-300342" type="indirect"></relation><relation active="#struct-300812" type="indirect"></relation><relation active="#struct-302313" type="indirect"></relation></listRelation><tutelles><tutelle active="#struct-11769" type="direct"><org type="laboratory" xml:id="struct-11769" status="VALID"><idno type="RNSR">199814131Y</idno><orgName>Laboratoire Génie Industriel - EA 2606</orgName><orgName type="acronym">LGI</orgName><desc><address><addrLine>CentraleSupélec - Grande Voie des Vignes - 92295 Chatenay-Malabry</addrLine><country key="FR"></country></address><ref type="url">http://www.lgi.ecp.fr</ref></desc><listRelation><relation active="#struct-411575" type="direct"></relation></listRelation></org></tutelle><tutelle active="#struct-411575" type="indirect"><org type="institution" xml:id="struct-411575" status="VALID"><orgName>CentraleSupélec</orgName><desc><address><addrLine>3, rue Joliot Curie,Plateau de Moulon,91192 GIF-SUR-YVETTE Cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.centralesupelec.fr</ref></desc></org></tutelle><tutelle active="#struct-161195" type="direct"><org type="laboratory" xml:id="struct-161195" status="VALID"><orgName>Chaire Sciences des Systèmes et Défis Energétiques EDF/ECP/Supélec</orgName><orgName type="acronym">SSEC</orgName><desc><address><country key="FR"></country></address></desc><listRelation><relation active="#struct-300342" type="direct"></relation><relation active="#struct-300812" type="direct"></relation><relation active="#struct-302313" type="direct"></relation><relation active="#struct-411575" type="direct"></relation></listRelation></org></tutelle><tutelle active="#struct-300342" type="indirect"><org type="institution" xml:id="struct-300342" status="VALID"><orgName>Ecole Centrale Paris</orgName><desc><address><country key="FR"></country></address></desc></org></tutelle><tutelle active="#struct-300812" type="indirect"><org type="institution" xml:id="struct-300812" status="VALID"><orgName>SUPELEC</orgName><desc><address><country key="FR"></country></address></desc></org></tutelle><tutelle active="#struct-302313" type="indirect"><org type="institution" xml:id="struct-302313" status="VALID"><orgName>Electricité de France Recherche et Développement</orgName><orgName type="acronym">EDF R&D</orgName><desc><address><addrLine>7 Boulevard Gaspard Monge 91120 Palaiseau</addrLine><country key="FR"></country></address></desc></org></tutelle></tutelles></hal:affiliation><country>France</country></affiliation></author><author><name sortKey="Kang, Rui" sort="Kang, Rui" uniqKey="Kang R" first="Rui" last="Kang">Rui Kang</name><affiliation wicri:level="1"><hal:affiliation type="laboratory" xml:id="struct-184330" status="VALID"> <orgName>University of Pittsburgh [Pittsburg]</orgName> <desc> <address> <addrLine>4200 Fifth Avenue Pittsburgh, PA 15260</addrLine> <country key="US"></country> </address> <ref type="url">http://www.pitt.edu/</ref> </desc> <listRelation> <relation active="#struct-378064" type="direct"></relation> </listRelation> <tutelles><tutelle active="#struct-378064" type="direct"><org type="institution" xml:id="struct-378064" status="INCOMING"> <orgName>University of Pittsburgh</orgName> <desc> <address> <country key="FR"></country> </address> </desc> </org></tutelle></tutelles></hal:affiliation><country>États-Unis</country><placeName><settlement type="city">Pittsburgh</settlement><region type="state">Pennsylvanie</region></placeName><orgName type="university">Université de Pittsburgh</orgName></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">HAL</idno><idno type="RBID">Hal:hal-01632275</idno><idno type="halId">hal-01632275</idno><idno type="halUri">https://hal.archives-ouvertes.fr/hal-01632275</idno><idno type="url">https://hal.archives-ouvertes.fr/hal-01632275</idno><idno type="doi">10.1177/1748006X16683321</idno><date when="2017-02-15">2017-02-15</date><idno type="wicri:Area/Hal/Corpus">000041</idno><idno type="wicri:Area/Hal/Curation">000041</idno><idno type="wicri:Area/Hal/Checkpoint">000026</idno><idno type="wicri:explorRef" wicri:stream="Hal" wicri:step="Checkpoint">000026</idno><idno type="wicri:doubleKey">1748-006X:2017:Zeng Z:a:hierarchical:decision</idno><idno type="wicri:Area/Main/Merge">000026</idno><idno type="wicri:Area/Main/Curation">000026</idno><idno type="wicri:Area/Main/Exploration">000026</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">A hierarchical decision-making framework for the assessment of the prediction capability of prognostic methods</title><author><name sortKey="Zeng, Zhiguo" sort="Zeng, Zhiguo" uniqKey="Zeng Z" first="Zhiguo" last="Zeng">Zhiguo Zeng</name><affiliation wicri:level="1"><hal:affiliation type="laboratory" xml:id="struct-11769" status="VALID"><idno type="RNSR">199814131Y</idno><orgName>Laboratoire Génie Industriel - EA 2606</orgName><orgName type="acronym">LGI</orgName><desc><address><addrLine>CentraleSupélec - Grande Voie des Vignes - 92295 Chatenay-Malabry</addrLine><country key="FR"></country></address><ref type="url">http://www.lgi.ecp.fr</ref></desc><listRelation><relation active="#struct-411575" type="direct"></relation></listRelation><tutelles><tutelle active="#struct-411575" type="direct"><org type="institution" xml:id="struct-411575" status="VALID"><orgName>CentraleSupélec</orgName><desc><address><addrLine>3, rue Joliot Curie,Plateau de Moulon,91192 GIF-SUR-YVETTE Cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.centralesupelec.fr</ref></desc></org></tutelle></tutelles></hal:affiliation><country>France</country></affiliation></author><author><name sortKey="Di Maio, Francesco" sort="Di Maio, Francesco" uniqKey="Di Maio F" first="Francesco" last="Di Maio">Francesco Di Maio</name><affiliation wicri:level="1"><hal:affiliation type="laboratory" xml:id="struct-161209" status="INCOMING"><orgName>Dipartimento di Energia</orgName><desc><address><country key="IT"></country></address></desc><listRelation><relation active="#struct-125443" type="direct"></relation></listRelation><tutelles><tutelle active="#struct-125443" type="direct"><org type="institution" xml:id="struct-125443" status="VALID"><orgName>Politecnico di Milano [Milan]</orgName><desc><address><addrLine>Piazza Leonardo da Vinci, 32 20133 Milano</addrLine><country key="IT"></country></address><ref type="url">http://www.polimi.it/</ref></desc></org></tutelle></tutelles></hal:affiliation><country>Italie</country></affiliation></author><author><name sortKey="Zio, Enrico" sort="Zio, Enrico" uniqKey="Zio E" first="Enrico" last="Zio">Enrico Zio</name><affiliation wicri:level="1"><hal:affiliation type="researchteam" xml:id="struct-391008" status="INCOMING"><orgName>Chaire Sciences des Systèmes et Défis Energétiques EDF/ECP/Supélec</orgName><desc><address><country key="FR"></country></address></desc><listRelation><relation active="#struct-11769" type="direct"></relation><relation active="#struct-411575" type="indirect"></relation><relation active="#struct-161195" type="direct"></relation><relation active="#struct-300342" type="indirect"></relation><relation active="#struct-300812" type="indirect"></relation><relation active="#struct-302313" type="indirect"></relation></listRelation><tutelles><tutelle active="#struct-11769" type="direct"><org type="laboratory" xml:id="struct-11769" status="VALID"><idno type="RNSR">199814131Y</idno><orgName>Laboratoire Génie Industriel - EA 2606</orgName><orgName type="acronym">LGI</orgName><desc><address><addrLine>CentraleSupélec - Grande Voie des Vignes - 92295 Chatenay-Malabry</addrLine><country key="FR"></country></address><ref type="url">http://www.lgi.ecp.fr</ref></desc><listRelation><relation active="#struct-411575" type="direct"></relation></listRelation></org></tutelle><tutelle active="#struct-411575" type="indirect"><org type="institution" xml:id="struct-411575" status="VALID"><orgName>CentraleSupélec</orgName><desc><address><addrLine>3, rue Joliot Curie,Plateau de Moulon,91192 GIF-SUR-YVETTE Cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.centralesupelec.fr</ref></desc></org></tutelle><tutelle active="#struct-161195" type="direct"><org type="laboratory" xml:id="struct-161195" status="VALID"><orgName>Chaire Sciences des Systèmes et Défis Energétiques EDF/ECP/Supélec</orgName><orgName type="acronym">SSEC</orgName><desc><address><country key="FR"></country></address></desc><listRelation><relation active="#struct-300342" type="direct"></relation><relation active="#struct-300812" type="direct"></relation><relation active="#struct-302313" type="direct"></relation><relation active="#struct-411575" type="direct"></relation></listRelation></org></tutelle><tutelle active="#struct-300342" type="indirect"><org type="institution" xml:id="struct-300342" status="VALID"><orgName>Ecole Centrale Paris</orgName><desc><address><country key="FR"></country></address></desc></org></tutelle><tutelle active="#struct-300812" type="indirect"><org type="institution" xml:id="struct-300812" status="VALID"><orgName>SUPELEC</orgName><desc><address><country key="FR"></country></address></desc></org></tutelle><tutelle active="#struct-302313" type="indirect"><org type="institution" xml:id="struct-302313" status="VALID"><orgName>Electricité de France Recherche et Développement</orgName><orgName type="acronym">EDF R&D</orgName><desc><address><addrLine>7 Boulevard Gaspard Monge 91120 Palaiseau</addrLine><country key="FR"></country></address></desc></org></tutelle></tutelles></hal:affiliation><country>France</country></affiliation></author><author><name sortKey="Kang, Rui" sort="Kang, Rui" uniqKey="Kang R" first="Rui" last="Kang">Rui Kang</name><affiliation wicri:level="1"><hal:affiliation type="laboratory" xml:id="struct-184330" status="VALID"> <orgName>University of Pittsburgh [Pittsburg]</orgName> <desc> <address> <addrLine>4200 Fifth Avenue Pittsburgh, PA 15260</addrLine> <country key="US"></country> </address> <ref type="url">http://www.pitt.edu/</ref> </desc> <listRelation> <relation active="#struct-378064" type="direct"></relation> </listRelation> <tutelles><tutelle active="#struct-378064" type="direct"><org type="institution" xml:id="struct-378064" status="INCOMING"> <orgName>University of Pittsburgh</orgName> <desc> <address> <country key="FR"></country> </address> </desc> </org></tutelle></tutelles></hal:affiliation><country>États-Unis</country><placeName><settlement type="city">Pittsburgh</settlement><region type="state">Pennsylvanie</region></placeName><orgName type="university">Université de Pittsburgh</orgName></affiliation></author></analytic><idno type="DOI">10.1177/1748006X16683321</idno><series><title level="j">Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability</title><idno type="ISSN">1748-006X</idno><imprint><date type="datePub">2017-02-15</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">8 In Prognostics and Health Management (PHM), the prediction capability of a prognostic method refers to its 9 ability to provide trustable predictions of the Remaining Useful Life (RUL), with the quality characteristics 10 required by the related maintenance decision making. The prediction capability heavily influences the decision 11 maker's attitude towards taking the risk of using the predicted RUL to inform the maintenance decisions. In this 12 paper, a four-layer, top-down, hierarchical decision making framework is proposed to assess the prediction 13 capability of prognostic methods. In the framework, prediction capability is broken down into two criteria (Layer 2), 14 six sub-criteria (Layer 3) and 19 basic sub-criteria (Layer 4). Based on the hierarchical framework, a bottom-up, 15 quantitative approach is developed for the assessment of the prediction capability, using the information and data 16 collected at the Layer-4 basic sub-criteria level. Analytical Hierarchical Process (AHP) is applied for the evaluation 17 and aggregation of the sub-criteria and Support Vector Machine (SVM) is applied to develop a classification-based 18 approach for prediction capability assessment. The framework and quantitative approach are applied on a simulated 19 case study to assess the prediction capabilities of three prognostic methods of literature: fuzzy similarity, 20 feed-forward neural network and hidden semi-Markov model. The results show the feasibility of the practical 21 application of the framework and its quantitative assessment approach, and that the assessed prediction capability 22 can be used to support the selection of the suitable prognostic method for a given application. </div></front></TEI><affiliations><list><country><li>France</li><li>Italie</li><li>États-Unis</li></country><region><li>Pennsylvanie</li></region><settlement><li>Pittsburgh</li></settlement><orgName><li>Université de Pittsburgh</li></orgName></list><tree><country name="France"><noRegion><name sortKey="Zeng, Zhiguo" sort="Zeng, Zhiguo" uniqKey="Zeng Z" first="Zhiguo" last="Zeng">Zhiguo Zeng</name></noRegion><name sortKey="Zio, Enrico" sort="Zio, Enrico" uniqKey="Zio E" first="Enrico" last="Zio">Enrico Zio</name></country><country name="Italie"><noRegion><name sortKey="Di Maio, Francesco" sort="Di Maio, Francesco" uniqKey="Di Maio F" first="Francesco" last="Di Maio">Francesco Di Maio</name></noRegion></country><country name="États-Unis"><region name="Pennsylvanie"><name sortKey="Kang, Rui" sort="Kang, Rui" uniqKey="Kang R" first="Rui" last="Kang">Rui Kang</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Amérique/explor/PittsburghV1/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000026 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 000026 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Wicri/Amérique
|area= PittsburghV1
|flux= Main
|étape= Exploration
|type= RBID
|clé= Hal:hal-01632275
|texte= A hierarchical decision-making framework for the assessment of the prediction capability of prognostic methods
}}
| This area was generated with Dilib version V0.6.38. |  |