An FMEA Risk Assessment Method Based on Social Networks Considering Expert Clustering and Risk Attitudes
Failure mode and effect analysis (FMEA) method has been widely utilized to solve the problem of risk assessment in all walks of life. An FMEA decision support model considering expert clustering and risk attitude is constructed. First, expert risk assessment information is processed in cloud environ...
Gespeichert in:
| Veröffentlicht in: | IEEE transactions on engineering management 2024, Vol.71, p.10783-10796 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 10796 |
|---|---|
| container_issue | |
| container_start_page | 10783 |
| container_title | IEEE transactions on engineering management |
| container_volume | 71 |
| creator | Liu, Peide Xu, Yiqiao Li, Ying Geng, Yushui |
| description | Failure mode and effect analysis (FMEA) method has been widely utilized to solve the problem of risk assessment in all walks of life. An FMEA decision support model considering expert clustering and risk attitude is constructed. First, expert risk assessment information is processed in cloud environment. The clustering behavior of experts is simulated based on trust relationship, opinion similarity, and risk attitude similarity. Second, consensus opinions are formed through opinion evolution, and the group weight determination model is constructed considering the group size and consensus level. Finally, a linear programming model minimizing individual regret is used to solve the risk factor (RF) weight problem. Combined with regret theory and the TODIM method considering finite rationality, the priority of risk is determined. The novel FMEA approach is applied to address reliability management problem of smart bracelets. Sensitivity and comparative analyses demonstrated the effectiveness and superiority of this method and enrich the theoretical research of the FMEA approach. |
| doi_str_mv | 10.1109/TEM.2024.3402949 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_crossref_primary_10_1109_TEM_2024_3402949</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>10536621</ieee_id><sourcerecordid>3065465547</sourcerecordid><originalsourceid>FETCH-LOGICAL-c245t-e0074d4948b492e5e75f6dedcd9d5981114a52a3792c9459c781829c657a711b3</originalsourceid><addsrcrecordid>eNpNkDFPwzAQRi0EEqWwMzBYYk6xHTuJxxClgNSCBGW20vhK05a4-BwB_55U6cB0utP7vpMeIdecTThn-m5RzieCCTmJJRNa6hMy4kplEWOSnZIRYzyLdKz5OblA3PSrVIKNyDpv6XRe5vS1wS3NEQHxE9pA5xDWztL7CsFS19I3VzfVjj5D-HZ-i7RwLTYWfNN-0PJnDz7QYtdhGC5Va4-NITShs4CX5GxV7RCujnNM3qfloniMZi8PT0U-i2ohVYiAsVRaqWW2lFqAglStEgu2ttoqnXHOZaVEFada1FoqXacZz4SuE5VWKefLeExuh969d18dYDAb1_m2f2liliiZKCXTnmIDVXuH6GFl9r75rPyv4cwcfJrepzn4NEeffeRmiDQA8A9XcZIIHv8BBm1wCA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3065465547</pqid></control><display><type>article</type><title>An FMEA Risk Assessment Method Based on Social Networks Considering Expert Clustering and Risk Attitudes</title><source>IEEE Electronic Library (IEL)</source><creator>Liu, Peide ; Xu, Yiqiao ; Li, Ying ; Geng, Yushui</creator><creatorcontrib>Liu, Peide ; Xu, Yiqiao ; Li, Ying ; Geng, Yushui</creatorcontrib><description>Failure mode and effect analysis (FMEA) method has been widely utilized to solve the problem of risk assessment in all walks of life. An FMEA decision support model considering expert clustering and risk attitude is constructed. First, expert risk assessment information is processed in cloud environment. The clustering behavior of experts is simulated based on trust relationship, opinion similarity, and risk attitude similarity. Second, consensus opinions are formed through opinion evolution, and the group weight determination model is constructed considering the group size and consensus level. Finally, a linear programming model minimizing individual regret is used to solve the risk factor (RF) weight problem. Combined with regret theory and the TODIM method considering finite rationality, the priority of risk is determined. The novel FMEA approach is applied to address reliability management problem of smart bracelets. Sensitivity and comparative analyses demonstrated the effectiveness and superiority of this method and enrich the theoretical research of the FMEA approach.</description><identifier>ISSN: 0018-9391</identifier><identifier>EISSN: 1558-0040</identifier><identifier>DOI: 10.1109/TEM.2024.3402949</identifier><identifier>CODEN: IEEMA4</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Attitudes ; Clustering ; Comparative analysis ; Decision theory ; Expert clustering ; failure mode and effect analysis (FMEA) ; Failure modes ; Frequency modulation ; Linear programming ; Psychology ; Quality management ; Radio frequency ; Reliability ; Risk assessment ; risk attitude ; Risk factors ; Risk management ; Similarity ; social network ; Social networking (online) ; Social networks ; TODIM</subject><ispartof>IEEE transactions on engineering management, 2024, Vol.71, p.10783-10796</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c245t-e0074d4948b492e5e75f6dedcd9d5981114a52a3792c9459c781829c657a711b3</cites><orcidid>0000-0001-5048-8145 ; 0000-0001-5926-5538 ; 0009-0001-7587-4242 ; 0000-0002-4780-0529</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10536621$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,4024,27923,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10536621$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Liu, Peide</creatorcontrib><creatorcontrib>Xu, Yiqiao</creatorcontrib><creatorcontrib>Li, Ying</creatorcontrib><creatorcontrib>Geng, Yushui</creatorcontrib><title>An FMEA Risk Assessment Method Based on Social Networks Considering Expert Clustering and Risk Attitudes</title><title>IEEE transactions on engineering management</title><addtitle>TEM</addtitle><description>Failure mode and effect analysis (FMEA) method has been widely utilized to solve the problem of risk assessment in all walks of life. An FMEA decision support model considering expert clustering and risk attitude is constructed. First, expert risk assessment information is processed in cloud environment. The clustering behavior of experts is simulated based on trust relationship, opinion similarity, and risk attitude similarity. Second, consensus opinions are formed through opinion evolution, and the group weight determination model is constructed considering the group size and consensus level. Finally, a linear programming model minimizing individual regret is used to solve the risk factor (RF) weight problem. Combined with regret theory and the TODIM method considering finite rationality, the priority of risk is determined. The novel FMEA approach is applied to address reliability management problem of smart bracelets. Sensitivity and comparative analyses demonstrated the effectiveness and superiority of this method and enrich the theoretical research of the FMEA approach.</description><subject>Attitudes</subject><subject>Clustering</subject><subject>Comparative analysis</subject><subject>Decision theory</subject><subject>Expert clustering</subject><subject>failure mode and effect analysis (FMEA)</subject><subject>Failure modes</subject><subject>Frequency modulation</subject><subject>Linear programming</subject><subject>Psychology</subject><subject>Quality management</subject><subject>Radio frequency</subject><subject>Reliability</subject><subject>Risk assessment</subject><subject>risk attitude</subject><subject>Risk factors</subject><subject>Risk management</subject><subject>Similarity</subject><subject>social network</subject><subject>Social networking (online)</subject><subject>Social networks</subject><subject>TODIM</subject><issn>0018-9391</issn><issn>1558-0040</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkDFPwzAQRi0EEqWwMzBYYk6xHTuJxxClgNSCBGW20vhK05a4-BwB_55U6cB0utP7vpMeIdecTThn-m5RzieCCTmJJRNa6hMy4kplEWOSnZIRYzyLdKz5OblA3PSrVIKNyDpv6XRe5vS1wS3NEQHxE9pA5xDWztL7CsFS19I3VzfVjj5D-HZ-i7RwLTYWfNN-0PJnDz7QYtdhGC5Va4-NITShs4CX5GxV7RCujnNM3qfloniMZi8PT0U-i2ohVYiAsVRaqWW2lFqAglStEgu2ttoqnXHOZaVEFada1FoqXacZz4SuE5VWKefLeExuh969d18dYDAb1_m2f2liliiZKCXTnmIDVXuH6GFl9r75rPyv4cwcfJrepzn4NEeffeRmiDQA8A9XcZIIHv8BBm1wCA</recordid><startdate>2024</startdate><enddate>2024</enddate><creator>Liu, Peide</creator><creator>Xu, Yiqiao</creator><creator>Li, Ying</creator><creator>Geng, Yushui</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>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-5048-8145</orcidid><orcidid>https://orcid.org/0000-0001-5926-5538</orcidid><orcidid>https://orcid.org/0009-0001-7587-4242</orcidid><orcidid>https://orcid.org/0000-0002-4780-0529</orcidid></search><sort><creationdate>2024</creationdate><title>An FMEA Risk Assessment Method Based on Social Networks Considering Expert Clustering and Risk Attitudes</title><author>Liu, Peide ; Xu, Yiqiao ; Li, Ying ; Geng, Yushui</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c245t-e0074d4948b492e5e75f6dedcd9d5981114a52a3792c9459c781829c657a711b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Attitudes</topic><topic>Clustering</topic><topic>Comparative analysis</topic><topic>Decision theory</topic><topic>Expert clustering</topic><topic>failure mode and effect analysis (FMEA)</topic><topic>Failure modes</topic><topic>Frequency modulation</topic><topic>Linear programming</topic><topic>Psychology</topic><topic>Quality management</topic><topic>Radio frequency</topic><topic>Reliability</topic><topic>Risk assessment</topic><topic>risk attitude</topic><topic>Risk factors</topic><topic>Risk management</topic><topic>Similarity</topic><topic>social network</topic><topic>Social networking (online)</topic><topic>Social networks</topic><topic>TODIM</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Peide</creatorcontrib><creatorcontrib>Xu, Yiqiao</creatorcontrib><creatorcontrib>Li, Ying</creatorcontrib><creatorcontrib>Geng, Yushui</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on engineering management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Liu, Peide</au><au>Xu, Yiqiao</au><au>Li, Ying</au><au>Geng, Yushui</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An FMEA Risk Assessment Method Based on Social Networks Considering Expert Clustering and Risk Attitudes</atitle><jtitle>IEEE transactions on engineering management</jtitle><stitle>TEM</stitle><date>2024</date><risdate>2024</risdate><volume>71</volume><spage>10783</spage><epage>10796</epage><pages>10783-10796</pages><issn>0018-9391</issn><eissn>1558-0040</eissn><coden>IEEMA4</coden><abstract>Failure mode and effect analysis (FMEA) method has been widely utilized to solve the problem of risk assessment in all walks of life. An FMEA decision support model considering expert clustering and risk attitude is constructed. First, expert risk assessment information is processed in cloud environment. The clustering behavior of experts is simulated based on trust relationship, opinion similarity, and risk attitude similarity. Second, consensus opinions are formed through opinion evolution, and the group weight determination model is constructed considering the group size and consensus level. Finally, a linear programming model minimizing individual regret is used to solve the risk factor (RF) weight problem. Combined with regret theory and the TODIM method considering finite rationality, the priority of risk is determined. The novel FMEA approach is applied to address reliability management problem of smart bracelets. Sensitivity and comparative analyses demonstrated the effectiveness and superiority of this method and enrich the theoretical research of the FMEA approach.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TEM.2024.3402949</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0001-5048-8145</orcidid><orcidid>https://orcid.org/0000-0001-5926-5538</orcidid><orcidid>https://orcid.org/0009-0001-7587-4242</orcidid><orcidid>https://orcid.org/0000-0002-4780-0529</orcidid></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 0018-9391 |
| ispartof | IEEE transactions on engineering management, 2024, Vol.71, p.10783-10796 |
| issn | 0018-9391 1558-0040 |
| language | eng |
| recordid | cdi_crossref_primary_10_1109_TEM_2024_3402949 |
| source | IEEE Electronic Library (IEL) |
| subjects | Attitudes Clustering Comparative analysis Decision theory Expert clustering failure mode and effect analysis (FMEA) Failure modes Frequency modulation Linear programming Psychology Quality management Radio frequency Reliability Risk assessment risk attitude Risk factors Risk management Similarity social network Social networking (online) Social networks TODIM |
| title | An FMEA Risk Assessment Method Based on Social Networks Considering Expert Clustering and Risk Attitudes |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-29T11%3A07%3A25IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=An%20FMEA%20Risk%20Assessment%20Method%20Based%20on%20Social%20Networks%20Considering%20Expert%20Clustering%20and%20Risk%20Attitudes&rft.jtitle=IEEE%20transactions%20on%20engineering%20management&rft.au=Liu,%20Peide&rft.date=2024&rft.volume=71&rft.spage=10783&rft.epage=10796&rft.pages=10783-10796&rft.issn=0018-9391&rft.eissn=1558-0040&rft.coden=IEEMA4&rft_id=info:doi/10.1109/TEM.2024.3402949&rft_dat=%3Cproquest_RIE%3E3065465547%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3065465547&rft_id=info:pmid/&rft_ieee_id=10536621&rfr_iscdi=true |