Risk-Based Maintenance Strategies on Fishing Vessel Refrigeration Systems Using Fuzzy-FMEA
Applying the fuzzy logic method to FMEA and its correlation with performance investigations is rarely applied in analyzing refrigeration system risk. The aim of this study is investigate the refrigeration system performance and analyze the risk of failure mode in the performance of the refrigeration...
Gespeichert in:
| Veröffentlicht in: | Journal of failure analysis and prevention 2024-04, Vol.24 (2), p.855-876 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 876 |
|---|---|
| container_issue | 2 |
| container_start_page | 855 |
| container_title | Journal of failure analysis and prevention |
| container_volume | 24 |
| creator | Siahaan, Juniawan Preston Yaqin, Rizqi Ilmal Priharanto, Yuniar Endri Abrori, M. Zaki Latif Siswantoro, Nurhadi |
| description | Applying the fuzzy logic method to FMEA and its correlation with performance investigations is rarely applied in analyzing refrigeration system risk. The aim of this study is investigate the refrigeration system performance and analyze the risk of failure mode in the performance of the refrigeration system using the fuzzy-FMEA method. In calculating performance, the COP parameter is needed. Prioritization of failure modes uses conventional FMEA (C-FMEA) and fuzzy-based FMEA (Fuzzy-FMEA), which produces conventional RPN (C-RPN) and fuzzy-RPN (F-RPN). Pareto diagrams are used to classify RPN categories which are the main causes. The result of the study is that the calculation of the refrigeration system performance shows a decreasing trend with increasing operating time. In the risk analysis, it was found that the F
21
(evaporator) failure has the same rating, and the highest is C-RPN (252) and F-RPN (750). Five categories need to be mitigated. The application of fuzzy-FMEA determines the critical failure priority of the evaporator. The results of this study provide new insights into developing engine performance investigations by determining critical failure modes to get mitigation quickly by minimizing expert opinion expertise. |
| doi_str_mv | 10.1007/s11668-024-01878-x |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_3039886410</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3039886410</sourcerecordid><originalsourceid>FETCH-LOGICAL-c270t-1f3f7a577f99bdc378904b4b0581f7cd30a4b81ed42523ad9f82be65f863bc083</originalsourceid><addsrcrecordid>eNp9kE1LAzEQhoMoWKt_wNOC52i-dpM91mJVaBFa68FLyO4mNbXdrZkttP31pq7gzdMMzPPOMA9C15TcUkLkHVCaZQoTJjChSiq8O0E9KpnCaSbFaexTIbEkLD9HFwBLQnhKBeuh96mHT3xvwFbJxPi6tbWpS5vM2mBau_AWkqZORh4-fL1I3iyAXSVT64Jf2Ej4OJztobVrSOZwREbbw2GPR5OHwSU6c2YF9uq39tF89PA6fMLjl8fn4WCMSyZJi6njTppUSpfnRVVyqXIiClGQVFEny4oTIwpFbSVYyripcqdYYbPUqYwXJVG8j266vZvQfG0ttHrZbEMdT2pOeK5UJiiJFOuoMjQAwTq9CX5twl5Too8OdedQR4f6x6HexRDvQhDhOn78t_qf1DditHUR</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3039886410</pqid></control><display><type>article</type><title>Risk-Based Maintenance Strategies on Fishing Vessel Refrigeration Systems Using Fuzzy-FMEA</title><source>SpringerNature Journals</source><creator>Siahaan, Juniawan Preston ; Yaqin, Rizqi Ilmal ; Priharanto, Yuniar Endri ; Abrori, M. Zaki Latif ; Siswantoro, Nurhadi</creator><creatorcontrib>Siahaan, Juniawan Preston ; Yaqin, Rizqi Ilmal ; Priharanto, Yuniar Endri ; Abrori, M. Zaki Latif ; Siswantoro, Nurhadi</creatorcontrib><description>Applying the fuzzy logic method to FMEA and its correlation with performance investigations is rarely applied in analyzing refrigeration system risk. The aim of this study is investigate the refrigeration system performance and analyze the risk of failure mode in the performance of the refrigeration system using the fuzzy-FMEA method. In calculating performance, the COP parameter is needed. Prioritization of failure modes uses conventional FMEA (C-FMEA) and fuzzy-based FMEA (Fuzzy-FMEA), which produces conventional RPN (C-RPN) and fuzzy-RPN (F-RPN). Pareto diagrams are used to classify RPN categories which are the main causes. The result of the study is that the calculation of the refrigeration system performance shows a decreasing trend with increasing operating time. In the risk analysis, it was found that the F
21
(evaporator) failure has the same rating, and the highest is C-RPN (252) and F-RPN (750). Five categories need to be mitigated. The application of fuzzy-FMEA determines the critical failure priority of the evaporator. The results of this study provide new insights into developing engine performance investigations by determining critical failure modes to get mitigation quickly by minimizing expert opinion expertise.</description><identifier>ISSN: 1547-7029</identifier><identifier>EISSN: 1728-5674</identifier><identifier>EISSN: 1864-1245</identifier><identifier>DOI: 10.1007/s11668-024-01878-x</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Characterization and Evaluation of Materials ; Chemistry and Materials Science ; Classical Mechanics ; Corrosion and Coatings ; Evaporators ; Failure modes ; Fuzzy logic ; Fuzzy systems ; Materials Science ; Mathematical analysis ; Original Research Article ; Quality Control ; Refrigeration ; Reliability ; Risk analysis ; Safety and Risk ; Solid Mechanics ; Tribology</subject><ispartof>Journal of failure analysis and prevention, 2024-04, Vol.24 (2), p.855-876</ispartof><rights>ASM International 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c270t-1f3f7a577f99bdc378904b4b0581f7cd30a4b81ed42523ad9f82be65f863bc083</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Siahaan, Juniawan Preston</creatorcontrib><creatorcontrib>Yaqin, Rizqi Ilmal</creatorcontrib><creatorcontrib>Priharanto, Yuniar Endri</creatorcontrib><creatorcontrib>Abrori, M. Zaki Latif</creatorcontrib><creatorcontrib>Siswantoro, Nurhadi</creatorcontrib><title>Risk-Based Maintenance Strategies on Fishing Vessel Refrigeration Systems Using Fuzzy-FMEA</title><title>Journal of failure analysis and prevention</title><addtitle>J Fail. Anal. and Preven</addtitle><description>Applying the fuzzy logic method to FMEA and its correlation with performance investigations is rarely applied in analyzing refrigeration system risk. The aim of this study is investigate the refrigeration system performance and analyze the risk of failure mode in the performance of the refrigeration system using the fuzzy-FMEA method. In calculating performance, the COP parameter is needed. Prioritization of failure modes uses conventional FMEA (C-FMEA) and fuzzy-based FMEA (Fuzzy-FMEA), which produces conventional RPN (C-RPN) and fuzzy-RPN (F-RPN). Pareto diagrams are used to classify RPN categories which are the main causes. The result of the study is that the calculation of the refrigeration system performance shows a decreasing trend with increasing operating time. In the risk analysis, it was found that the F
21
(evaporator) failure has the same rating, and the highest is C-RPN (252) and F-RPN (750). Five categories need to be mitigated. The application of fuzzy-FMEA determines the critical failure priority of the evaporator. The results of this study provide new insights into developing engine performance investigations by determining critical failure modes to get mitigation quickly by minimizing expert opinion expertise.</description><subject>Characterization and Evaluation of Materials</subject><subject>Chemistry and Materials Science</subject><subject>Classical Mechanics</subject><subject>Corrosion and Coatings</subject><subject>Evaporators</subject><subject>Failure modes</subject><subject>Fuzzy logic</subject><subject>Fuzzy systems</subject><subject>Materials Science</subject><subject>Mathematical analysis</subject><subject>Original Research Article</subject><subject>Quality Control</subject><subject>Refrigeration</subject><subject>Reliability</subject><subject>Risk analysis</subject><subject>Safety and Risk</subject><subject>Solid Mechanics</subject><subject>Tribology</subject><issn>1547-7029</issn><issn>1728-5674</issn><issn>1864-1245</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kE1LAzEQhoMoWKt_wNOC52i-dpM91mJVaBFa68FLyO4mNbXdrZkttP31pq7gzdMMzPPOMA9C15TcUkLkHVCaZQoTJjChSiq8O0E9KpnCaSbFaexTIbEkLD9HFwBLQnhKBeuh96mHT3xvwFbJxPi6tbWpS5vM2mBau_AWkqZORh4-fL1I3iyAXSVT64Jf2Ej4OJztobVrSOZwREbbw2GPR5OHwSU6c2YF9uq39tF89PA6fMLjl8fn4WCMSyZJi6njTppUSpfnRVVyqXIiClGQVFEny4oTIwpFbSVYyripcqdYYbPUqYwXJVG8j266vZvQfG0ttHrZbEMdT2pOeK5UJiiJFOuoMjQAwTq9CX5twl5Too8OdedQR4f6x6HexRDvQhDhOn78t_qf1DditHUR</recordid><startdate>20240401</startdate><enddate>20240401</enddate><creator>Siahaan, Juniawan Preston</creator><creator>Yaqin, Rizqi Ilmal</creator><creator>Priharanto, Yuniar Endri</creator><creator>Abrori, M. Zaki Latif</creator><creator>Siswantoro, Nurhadi</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>8BQ</scope><scope>8FD</scope><scope>FR3</scope><scope>JG9</scope><scope>KR7</scope></search><sort><creationdate>20240401</creationdate><title>Risk-Based Maintenance Strategies on Fishing Vessel Refrigeration Systems Using Fuzzy-FMEA</title><author>Siahaan, Juniawan Preston ; Yaqin, Rizqi Ilmal ; Priharanto, Yuniar Endri ; Abrori, M. Zaki Latif ; Siswantoro, Nurhadi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c270t-1f3f7a577f99bdc378904b4b0581f7cd30a4b81ed42523ad9f82be65f863bc083</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Characterization and Evaluation of Materials</topic><topic>Chemistry and Materials Science</topic><topic>Classical Mechanics</topic><topic>Corrosion and Coatings</topic><topic>Evaporators</topic><topic>Failure modes</topic><topic>Fuzzy logic</topic><topic>Fuzzy systems</topic><topic>Materials Science</topic><topic>Mathematical analysis</topic><topic>Original Research Article</topic><topic>Quality Control</topic><topic>Refrigeration</topic><topic>Reliability</topic><topic>Risk analysis</topic><topic>Safety and Risk</topic><topic>Solid Mechanics</topic><topic>Tribology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Siahaan, Juniawan Preston</creatorcontrib><creatorcontrib>Yaqin, Rizqi Ilmal</creatorcontrib><creatorcontrib>Priharanto, Yuniar Endri</creatorcontrib><creatorcontrib>Abrori, M. Zaki Latif</creatorcontrib><creatorcontrib>Siswantoro, Nurhadi</creatorcontrib><collection>CrossRef</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Materials Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Journal of failure analysis and prevention</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Siahaan, Juniawan Preston</au><au>Yaqin, Rizqi Ilmal</au><au>Priharanto, Yuniar Endri</au><au>Abrori, M. Zaki Latif</au><au>Siswantoro, Nurhadi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Risk-Based Maintenance Strategies on Fishing Vessel Refrigeration Systems Using Fuzzy-FMEA</atitle><jtitle>Journal of failure analysis and prevention</jtitle><stitle>J Fail. Anal. and Preven</stitle><date>2024-04-01</date><risdate>2024</risdate><volume>24</volume><issue>2</issue><spage>855</spage><epage>876</epage><pages>855-876</pages><issn>1547-7029</issn><eissn>1728-5674</eissn><eissn>1864-1245</eissn><abstract>Applying the fuzzy logic method to FMEA and its correlation with performance investigations is rarely applied in analyzing refrigeration system risk. The aim of this study is investigate the refrigeration system performance and analyze the risk of failure mode in the performance of the refrigeration system using the fuzzy-FMEA method. In calculating performance, the COP parameter is needed. Prioritization of failure modes uses conventional FMEA (C-FMEA) and fuzzy-based FMEA (Fuzzy-FMEA), which produces conventional RPN (C-RPN) and fuzzy-RPN (F-RPN). Pareto diagrams are used to classify RPN categories which are the main causes. The result of the study is that the calculation of the refrigeration system performance shows a decreasing trend with increasing operating time. In the risk analysis, it was found that the F
21
(evaporator) failure has the same rating, and the highest is C-RPN (252) and F-RPN (750). Five categories need to be mitigated. The application of fuzzy-FMEA determines the critical failure priority of the evaporator. The results of this study provide new insights into developing engine performance investigations by determining critical failure modes to get mitigation quickly by minimizing expert opinion expertise.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s11668-024-01878-x</doi><tpages>22</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1547-7029 |
| ispartof | Journal of failure analysis and prevention, 2024-04, Vol.24 (2), p.855-876 |
| issn | 1547-7029 1728-5674 1864-1245 |
| language | eng |
| recordid | cdi_proquest_journals_3039886410 |
| source | SpringerNature Journals |
| subjects | Characterization and Evaluation of Materials Chemistry and Materials Science Classical Mechanics Corrosion and Coatings Evaporators Failure modes Fuzzy logic Fuzzy systems Materials Science Mathematical analysis Original Research Article Quality Control Refrigeration Reliability Risk analysis Safety and Risk Solid Mechanics Tribology |
| title | Risk-Based Maintenance Strategies on Fishing Vessel Refrigeration Systems Using Fuzzy-FMEA |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-22T20%3A23%3A40IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Risk-Based%20Maintenance%20Strategies%20on%20Fishing%20Vessel%20Refrigeration%20Systems%20Using%20Fuzzy-FMEA&rft.jtitle=Journal%20of%20failure%20analysis%20and%20prevention&rft.au=Siahaan,%20Juniawan%20Preston&rft.date=2024-04-01&rft.volume=24&rft.issue=2&rft.spage=855&rft.epage=876&rft.pages=855-876&rft.issn=1547-7029&rft.eissn=1728-5674&rft_id=info:doi/10.1007/s11668-024-01878-x&rft_dat=%3Cproquest_cross%3E3039886410%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3039886410&rft_id=info:pmid/&rfr_iscdi=true |