Optimal Maintenance Decision Based on Remaining Useful Lifetime Prediction for the Equipment Subject to Imperfect Maintenance
Focusing on the fact that the existing research on optimal maintenance decision for remaining useful lifetime (RUL) prediction and imperfect maintenance has low accuracy of RUL prediction and rationality of decision results, an optimal maintenance decision method based on RUL prediction for the equi...
Gespeichert in:
| Veröffentlicht in: | IEEE access 2020, Vol.8, p.6704-6716 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 6716 |
|---|---|
| container_issue | |
| container_start_page | 6704 |
| container_title | IEEE access |
| container_volume | 8 |
| creator | Chen, Yunxiang Wang, Zezhou Cai, Zhongyi |
| description | Focusing on the fact that the existing research on optimal maintenance decision for remaining useful lifetime (RUL) prediction and imperfect maintenance has low accuracy of RUL prediction and rationality of decision results, an optimal maintenance decision method based on RUL prediction for the equipment subject to imperfect maintenance is proposed in this paper. Firstly, the nonlinear Wiener process is used to characterize the degradation law of the equipment. Secondly, the imperfect maintenance model that meets the upper limit of the maintenance number is established based on the nonhomogeneous Poisson process. Then, based on the concept of the first hitting time, the probability density function (PDF) of the RUL is derived. Finally, based on the RUL prediction results, the optimal maintenance decision model for the equipment subject imperfect maintenance is constructed. Through the example verification and cost parameter sensitivity analysis, the proposed method can effectively improve the accuracy of the RUL prediction and the scientific of maintenance decision results, which has engineering application value. |
| doi_str_mv | 10.1109/ACCESS.2019.2963765 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_webof</sourceid><recordid>TN_cdi_webofscience_primary_000524687200006</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>8949355</ieee_id><doaj_id>oai_doaj_org_article_dc0b8ec664eb4720ba920155647acbda</doaj_id><sourcerecordid>2454956771</sourcerecordid><originalsourceid>FETCH-LOGICAL-c408t-13608a9366d15bf993221697b2f0a522dd02d49bc19471c0c24f653ecf3dd2793</originalsourceid><addsrcrecordid>eNqNUU1v1DAQjRBIVKW_oBdLHNFu_Z34WMICKy0qYunZcuxx8Wo3Th1HFQf-ex1SlR6Zi2fG783Xq6pLgteEYHV13bab_X5NMVFrqiSrpXhVnVEi1YoJJl-_8N9WF-N4wMWakhL1WfXnZsjhZI7omwl9ht70FtAnsGEMsUcfzQgOFecHnMp_6O_Q7Qh-OqJd8FCIgL4ncMHmGe1jQvkXoM39FIYT9Bntp-4ANqMc0fY0QPJz8KLTu-qNN8cRLp7e8-r28-Zn-3W1u_myba93K8txk1eESdwYxaR0RHReKUbnleqOemwEpc5h6rjqLFG8JhZbyr0UDKxnztFasfNqu9R10Rz0kMrG6beOJui_iZjutEk52CNoZ3HXgJWSQ8drijujymWFkLw2tnOm1Hq_1BpSvJ9gzPoQp9SX8TXlgish65oUFFtQNsVxTOCfuxKsZ9n0IpueZdNPshXWh4X1AF30ow1QjvTMLLIJymVTpiomC7r5f3QbsplVauPU50K9XKgB4B-lUVwxIdgjJ8u0yA</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2454956771</pqid></control><display><type>article</type><title>Optimal Maintenance Decision Based on Remaining Useful Lifetime Prediction for the Equipment Subject to Imperfect Maintenance</title><source>IEEE Open Access Journals</source><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Web of Science - Science Citation Index Expanded - 2020<img src="https://exlibris-pub.s3.amazonaws.com/fromwos-v2.jpg" /></source><creator>Chen, Yunxiang ; Wang, Zezhou ; Cai, Zhongyi</creator><creatorcontrib>Chen, Yunxiang ; Wang, Zezhou ; Cai, Zhongyi</creatorcontrib><description>Focusing on the fact that the existing research on optimal maintenance decision for remaining useful lifetime (RUL) prediction and imperfect maintenance has low accuracy of RUL prediction and rationality of decision results, an optimal maintenance decision method based on RUL prediction for the equipment subject to imperfect maintenance is proposed in this paper. Firstly, the nonlinear Wiener process is used to characterize the degradation law of the equipment. Secondly, the imperfect maintenance model that meets the upper limit of the maintenance number is established based on the nonhomogeneous Poisson process. Then, based on the concept of the first hitting time, the probability density function (PDF) of the RUL is derived. Finally, based on the RUL prediction results, the optimal maintenance decision model for the equipment subject imperfect maintenance is constructed. Through the example verification and cost parameter sensitivity analysis, the proposed method can effectively improve the accuracy of the RUL prediction and the scientific of maintenance decision results, which has engineering application value.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2019.2963765</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>PISCATAWAY: IEEE</publisher><subject>Computer Science ; Computer Science, Information Systems ; Cost analysis ; Degradation ; Economics ; Engineering ; Engineering, Electrical & Electronic ; imperfect maintenance ; Maintenance ; Maintenance decision ; Maintenance engineering ; Mathematical model ; nonhomogeneous Poisson process ; nonlinear Wiener process ; Parameter sensitivity ; Predictive models ; Probability density function ; Probability density functions ; Production ; remaining useful lifetime prediction ; Science & Technology ; Sensitivity analysis ; Statistical analysis ; Technology ; Telecommunications</subject><ispartof>IEEE access, 2020, Vol.8, p.6704-6716</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>true</woscitedreferencessubscribed><woscitedreferencescount>14</woscitedreferencescount><woscitedreferencesoriginalsourcerecordid>wos000524687200006</woscitedreferencesoriginalsourcerecordid><citedby>FETCH-LOGICAL-c408t-13608a9366d15bf993221697b2f0a522dd02d49bc19471c0c24f653ecf3dd2793</citedby><cites>FETCH-LOGICAL-c408t-13608a9366d15bf993221697b2f0a522dd02d49bc19471c0c24f653ecf3dd2793</cites><orcidid>0000-0003-4148-0496 ; 0000-0002-4722-5405</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8949355$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>315,781,785,865,2103,2115,4025,27638,27928,27929,27930,28253,54938</link.rule.ids></links><search><creatorcontrib>Chen, Yunxiang</creatorcontrib><creatorcontrib>Wang, Zezhou</creatorcontrib><creatorcontrib>Cai, Zhongyi</creatorcontrib><title>Optimal Maintenance Decision Based on Remaining Useful Lifetime Prediction for the Equipment Subject to Imperfect Maintenance</title><title>IEEE access</title><addtitle>Access</addtitle><addtitle>IEEE ACCESS</addtitle><description>Focusing on the fact that the existing research on optimal maintenance decision for remaining useful lifetime (RUL) prediction and imperfect maintenance has low accuracy of RUL prediction and rationality of decision results, an optimal maintenance decision method based on RUL prediction for the equipment subject to imperfect maintenance is proposed in this paper. Firstly, the nonlinear Wiener process is used to characterize the degradation law of the equipment. Secondly, the imperfect maintenance model that meets the upper limit of the maintenance number is established based on the nonhomogeneous Poisson process. Then, based on the concept of the first hitting time, the probability density function (PDF) of the RUL is derived. Finally, based on the RUL prediction results, the optimal maintenance decision model for the equipment subject imperfect maintenance is constructed. Through the example verification and cost parameter sensitivity analysis, the proposed method can effectively improve the accuracy of the RUL prediction and the scientific of maintenance decision results, which has engineering application value.</description><subject>Computer Science</subject><subject>Computer Science, Information Systems</subject><subject>Cost analysis</subject><subject>Degradation</subject><subject>Economics</subject><subject>Engineering</subject><subject>Engineering, Electrical & Electronic</subject><subject>imperfect maintenance</subject><subject>Maintenance</subject><subject>Maintenance decision</subject><subject>Maintenance engineering</subject><subject>Mathematical model</subject><subject>nonhomogeneous Poisson process</subject><subject>nonlinear Wiener process</subject><subject>Parameter sensitivity</subject><subject>Predictive models</subject><subject>Probability density function</subject><subject>Probability density functions</subject><subject>Production</subject><subject>remaining useful lifetime prediction</subject><subject>Science & Technology</subject><subject>Sensitivity analysis</subject><subject>Statistical analysis</subject><subject>Technology</subject><subject>Telecommunications</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>AOWDO</sourceid><sourceid>DOA</sourceid><recordid>eNqNUU1v1DAQjRBIVKW_oBdLHNFu_Z34WMICKy0qYunZcuxx8Wo3Th1HFQf-ex1SlR6Zi2fG783Xq6pLgteEYHV13bab_X5NMVFrqiSrpXhVnVEi1YoJJl-_8N9WF-N4wMWakhL1WfXnZsjhZI7omwl9ht70FtAnsGEMsUcfzQgOFecHnMp_6O_Q7Qh-OqJd8FCIgL4ncMHmGe1jQvkXoM39FIYT9Bntp-4ANqMc0fY0QPJz8KLTu-qNN8cRLp7e8-r28-Zn-3W1u_myba93K8txk1eESdwYxaR0RHReKUbnleqOemwEpc5h6rjqLFG8JhZbyr0UDKxnztFasfNqu9R10Rz0kMrG6beOJui_iZjutEk52CNoZ3HXgJWSQ8drijujymWFkLw2tnOm1Hq_1BpSvJ9gzPoQp9SX8TXlgish65oUFFtQNsVxTOCfuxKsZ9n0IpueZdNPshXWh4X1AF30ow1QjvTMLLIJymVTpiomC7r5f3QbsplVauPU50K9XKgB4B-lUVwxIdgjJ8u0yA</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Chen, Yunxiang</creator><creator>Wang, Zezhou</creator><creator>Cai, Zhongyi</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AOWDO</scope><scope>BLEPL</scope><scope>DTL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7SR</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-4148-0496</orcidid><orcidid>https://orcid.org/0000-0002-4722-5405</orcidid></search><sort><creationdate>2020</creationdate><title>Optimal Maintenance Decision Based on Remaining Useful Lifetime Prediction for the Equipment Subject to Imperfect Maintenance</title><author>Chen, Yunxiang ; Wang, Zezhou ; Cai, Zhongyi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c408t-13608a9366d15bf993221697b2f0a522dd02d49bc19471c0c24f653ecf3dd2793</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Computer Science</topic><topic>Computer Science, Information Systems</topic><topic>Cost analysis</topic><topic>Degradation</topic><topic>Economics</topic><topic>Engineering</topic><topic>Engineering, Electrical & Electronic</topic><topic>imperfect maintenance</topic><topic>Maintenance</topic><topic>Maintenance decision</topic><topic>Maintenance engineering</topic><topic>Mathematical model</topic><topic>nonhomogeneous Poisson process</topic><topic>nonlinear Wiener process</topic><topic>Parameter sensitivity</topic><topic>Predictive models</topic><topic>Probability density function</topic><topic>Probability density functions</topic><topic>Production</topic><topic>remaining useful lifetime prediction</topic><topic>Science & Technology</topic><topic>Sensitivity analysis</topic><topic>Statistical analysis</topic><topic>Technology</topic><topic>Telecommunications</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Yunxiang</creatorcontrib><creatorcontrib>Wang, Zezhou</creatorcontrib><creatorcontrib>Cai, Zhongyi</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Web of Science - Science Citation Index Expanded - 2020</collection><collection>Web of Science Core Collection</collection><collection>Science Citation Index Expanded</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>IEEE access</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Yunxiang</au><au>Wang, Zezhou</au><au>Cai, Zhongyi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimal Maintenance Decision Based on Remaining Useful Lifetime Prediction for the Equipment Subject to Imperfect Maintenance</atitle><jtitle>IEEE access</jtitle><stitle>Access</stitle><stitle>IEEE ACCESS</stitle><date>2020</date><risdate>2020</risdate><volume>8</volume><spage>6704</spage><epage>6716</epage><pages>6704-6716</pages><issn>2169-3536</issn><eissn>2169-3536</eissn><coden>IAECCG</coden><abstract>Focusing on the fact that the existing research on optimal maintenance decision for remaining useful lifetime (RUL) prediction and imperfect maintenance has low accuracy of RUL prediction and rationality of decision results, an optimal maintenance decision method based on RUL prediction for the equipment subject to imperfect maintenance is proposed in this paper. Firstly, the nonlinear Wiener process is used to characterize the degradation law of the equipment. Secondly, the imperfect maintenance model that meets the upper limit of the maintenance number is established based on the nonhomogeneous Poisson process. Then, based on the concept of the first hitting time, the probability density function (PDF) of the RUL is derived. Finally, based on the RUL prediction results, the optimal maintenance decision model for the equipment subject imperfect maintenance is constructed. Through the example verification and cost parameter sensitivity analysis, the proposed method can effectively improve the accuracy of the RUL prediction and the scientific of maintenance decision results, which has engineering application value.</abstract><cop>PISCATAWAY</cop><pub>IEEE</pub><doi>10.1109/ACCESS.2019.2963765</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0003-4148-0496</orcidid><orcidid>https://orcid.org/0000-0002-4722-5405</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 2169-3536 |
| ispartof | IEEE access, 2020, Vol.8, p.6704-6716 |
| issn | 2169-3536 2169-3536 |
| language | eng |
| recordid | cdi_webofscience_primary_000524687200006 |
| source | IEEE Open Access Journals; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Web of Science - Science Citation Index Expanded - 2020<img src="https://exlibris-pub.s3.amazonaws.com/fromwos-v2.jpg" /> |
| subjects | Computer Science Computer Science, Information Systems Cost analysis Degradation Economics Engineering Engineering, Electrical & Electronic imperfect maintenance Maintenance Maintenance decision Maintenance engineering Mathematical model nonhomogeneous Poisson process nonlinear Wiener process Parameter sensitivity Predictive models Probability density function Probability density functions Production remaining useful lifetime prediction Science & Technology Sensitivity analysis Statistical analysis Technology Telecommunications |
| title | Optimal Maintenance Decision Based on Remaining Useful Lifetime Prediction for the Equipment Subject to Imperfect Maintenance |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-14T17%3A43%3A46IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_webof&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Optimal%20Maintenance%20Decision%20Based%20on%20Remaining%20Useful%20Lifetime%20Prediction%20for%20the%20Equipment%20Subject%20to%20Imperfect%20Maintenance&rft.jtitle=IEEE%20access&rft.au=Chen,%20Yunxiang&rft.date=2020&rft.volume=8&rft.spage=6704&rft.epage=6716&rft.pages=6704-6716&rft.issn=2169-3536&rft.eissn=2169-3536&rft.coden=IAECCG&rft_id=info:doi/10.1109/ACCESS.2019.2963765&rft_dat=%3Cproquest_webof%3E2454956771%3C/proquest_webof%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2454956771&rft_id=info:pmid/&rft_ieee_id=8949355&rft_doaj_id=oai_doaj_org_article_dc0b8ec664eb4720ba920155647acbda&rfr_iscdi=true |