Composite multilinearity, epistemic uncertainty and risk achievement worth
► Under epistemic uncertainty a risk metric expected value differs from its nominal value. ► Separability and state-of-knowledge independence are necessary for coincidence. ► We extend Risk Achievement Worth to make it robust to epistemic uncertainty. Risk achievement worth is one of the most widely...
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Veröffentlicht in: | European journal of operational research 2012-10, Vol.222 (2), p.301-311 |
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description | ► Under epistemic uncertainty a risk metric expected value differs from its nominal value. ► Separability and state-of-knowledge independence are necessary for coincidence. ► We extend Risk Achievement Worth to make it robust to epistemic uncertainty.
Risk achievement worth is one of the most widely utilized importance measures. RAW is defined as the ratio of the risk metric value attained when a component has failed over the base case value of the risk metric. Traditionally, both the numerator and denominator are point estimates. Relevant literature has shown that inclusion of epistemic uncertainty (i) induces notable variability in the point estimate ranking and (ii) causes the expected value of the risk metric to differ from its nominal value. We investigate the conditions under which the equality of the nominal and expected values of a reliability risk metric holds. We then study how the presence of epistemic uncertainty affects RAW and the associated ranking. We propose an extension of RAW (called ERAW) which allows one to obtain a ranking robust to epistemic uncertainty. We discuss the properties of ERAW and the conditions under which it coincides with RAW. We apply our findings to a probabilistic risk assessment model developed for the safety analysis of NASA lunar space missions. |
doi_str_mv | 10.1016/j.ejor.2012.05.008 |
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Risk achievement worth is one of the most widely utilized importance measures. RAW is defined as the ratio of the risk metric value attained when a component has failed over the base case value of the risk metric. Traditionally, both the numerator and denominator are point estimates. Relevant literature has shown that inclusion of epistemic uncertainty (i) induces notable variability in the point estimate ranking and (ii) causes the expected value of the risk metric to differ from its nominal value. We investigate the conditions under which the equality of the nominal and expected values of a reliability risk metric holds. We then study how the presence of epistemic uncertainty affects RAW and the associated ranking. We propose an extension of RAW (called ERAW) which allows one to obtain a ranking robust to epistemic uncertainty. We discuss the properties of ERAW and the conditions under which it coincides with RAW. We apply our findings to a probabilistic risk assessment model developed for the safety analysis of NASA lunar space missions.</description><identifier>ISSN: 0377-2217</identifier><identifier>EISSN: 1872-6860</identifier><identifier>DOI: 10.1016/j.ejor.2012.05.008</identifier><identifier>CODEN: EJORDT</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Applied sciences ; Decision analysis ; Decision theory. Utility theory ; epistemic ; Epistemology ; Estimates ; Exact sciences and technology ; Expected values ; importance ; Importance measures ; MATHEMATICS AND COMPUTING ; NASA ; Operational research ; Operational research and scientific management ; Operational research. Management science ; Probabilistic risk assessment ; Ranking ; RAW ; Reliability analysis ; Reliability theory. Replacement problems ; Risk ; Risk analysis ; Risk assessment ; Risk theory. Actuarial science ; Space exploration ; Studies ; Uncertainty ; Uncertainty analysis</subject><ispartof>European journal of operational research, 2012-10, Vol.222 (2), p.301-311</ispartof><rights>2012 Elsevier B.V.</rights><rights>2015 INIST-CNRS</rights><rights>Copyright Elsevier Sequoia S.A. Oct 16, 2012</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c449t-ac69382fc731702adf7739ca0f87b984ff132648f56bd1c9828b2a467be7d9e3</citedby><cites>FETCH-LOGICAL-c449t-ac69382fc731702adf7739ca0f87b984ff132648f56bd1c9828b2a467be7d9e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.ejor.2012.05.008$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,315,782,786,887,3554,27933,27934,46004</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=26030357$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.osti.gov/biblio/1060424$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Borgonovo, E.</creatorcontrib><creatorcontrib>Smith, C.L.</creatorcontrib><creatorcontrib>Idaho National Laboratory (INL)</creatorcontrib><title>Composite multilinearity, epistemic uncertainty and risk achievement worth</title><title>European journal of operational research</title><description>► Under epistemic uncertainty a risk metric expected value differs from its nominal value. ► Separability and state-of-knowledge independence are necessary for coincidence. ► We extend Risk Achievement Worth to make it robust to epistemic uncertainty.
Risk achievement worth is one of the most widely utilized importance measures. RAW is defined as the ratio of the risk metric value attained when a component has failed over the base case value of the risk metric. Traditionally, both the numerator and denominator are point estimates. Relevant literature has shown that inclusion of epistemic uncertainty (i) induces notable variability in the point estimate ranking and (ii) causes the expected value of the risk metric to differ from its nominal value. We investigate the conditions under which the equality of the nominal and expected values of a reliability risk metric holds. We then study how the presence of epistemic uncertainty affects RAW and the associated ranking. We propose an extension of RAW (called ERAW) which allows one to obtain a ranking robust to epistemic uncertainty. We discuss the properties of ERAW and the conditions under which it coincides with RAW. We apply our findings to a probabilistic risk assessment model developed for the safety analysis of NASA lunar space missions.</description><subject>Applied sciences</subject><subject>Decision analysis</subject><subject>Decision theory. Utility theory</subject><subject>epistemic</subject><subject>Epistemology</subject><subject>Estimates</subject><subject>Exact sciences and technology</subject><subject>Expected values</subject><subject>importance</subject><subject>Importance measures</subject><subject>MATHEMATICS AND COMPUTING</subject><subject>NASA</subject><subject>Operational research</subject><subject>Operational research and scientific management</subject><subject>Operational research. Management science</subject><subject>Probabilistic risk assessment</subject><subject>Ranking</subject><subject>RAW</subject><subject>Reliability analysis</subject><subject>Reliability theory. Replacement problems</subject><subject>Risk</subject><subject>Risk analysis</subject><subject>Risk assessment</subject><subject>Risk theory. Actuarial science</subject><subject>Space exploration</subject><subject>Studies</subject><subject>Uncertainty</subject><subject>Uncertainty analysis</subject><issn>0377-2217</issn><issn>1872-6860</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><recordid>eNp90Utv1DAQB3ALgcRS-AKcIhASB5L6ET8icUErXlWlXnq3vM5Y65DYi-202m-Po604cODky2_GM_NH6C3BHcFEXE8dTDF1FBPaYd5hrJ6hHVGStkIJ_BztMJOypZTIl-hVzhPGmHDCd-hmH5dTzL5As6xz8bMPYJIv508NnHwusHjbrMFCKsaHcm5MGJvk86_G2KOHB1gglOYxpnJ8jV44M2d48_ReoftvX-_3P9rbu-8_919uW9v3Q2mNFQNT1FnJiMTUjE5KNliDnZKHQfXOEUZFrxwXh5HYQVF1oKYX8gByHIBdoXeXtjEXr7Oto9ujjSGALZpggXvaV_Txgk4p_l4hF734bGGeTYC45urqCJwOnFb6_h86xTWFukFVtF6XM86qohdlU8w5gdOn5BeTzhXpLQI96S0CvUWgMdc1glr04am1ydbMLplgff5bSQVmmHFZ3eeLg3q2Bw9pWwvq0Ueftq3G6P_3zR-Vf5u6</recordid><startdate>20121016</startdate><enddate>20121016</enddate><creator>Borgonovo, E.</creator><creator>Smith, C.L.</creator><general>Elsevier B.V</general><general>Elsevier</general><general>Elsevier Sequoia S.A</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7TA</scope><scope>JG9</scope><scope>OTOTI</scope></search><sort><creationdate>20121016</creationdate><title>Composite multilinearity, epistemic uncertainty and risk achievement worth</title><author>Borgonovo, E. ; Smith, C.L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c449t-ac69382fc731702adf7739ca0f87b984ff132648f56bd1c9828b2a467be7d9e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Applied sciences</topic><topic>Decision analysis</topic><topic>Decision theory. Utility theory</topic><topic>epistemic</topic><topic>Epistemology</topic><topic>Estimates</topic><topic>Exact sciences and technology</topic><topic>Expected values</topic><topic>importance</topic><topic>Importance measures</topic><topic>MATHEMATICS AND COMPUTING</topic><topic>NASA</topic><topic>Operational research</topic><topic>Operational research and scientific management</topic><topic>Operational research. Management science</topic><topic>Probabilistic risk assessment</topic><topic>Ranking</topic><topic>RAW</topic><topic>Reliability analysis</topic><topic>Reliability theory. Replacement problems</topic><topic>Risk</topic><topic>Risk analysis</topic><topic>Risk assessment</topic><topic>Risk theory. Actuarial science</topic><topic>Space exploration</topic><topic>Studies</topic><topic>Uncertainty</topic><topic>Uncertainty analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Borgonovo, E.</creatorcontrib><creatorcontrib>Smith, C.L.</creatorcontrib><creatorcontrib>Idaho National Laboratory (INL)</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems 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>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Materials Business File</collection><collection>Materials Research Database</collection><collection>OSTI.GOV</collection><jtitle>European journal of operational research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Borgonovo, E.</au><au>Smith, C.L.</au><aucorp>Idaho National Laboratory (INL)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Composite multilinearity, epistemic uncertainty and risk achievement worth</atitle><jtitle>European journal of operational research</jtitle><date>2012-10-16</date><risdate>2012</risdate><volume>222</volume><issue>2</issue><spage>301</spage><epage>311</epage><pages>301-311</pages><issn>0377-2217</issn><eissn>1872-6860</eissn><coden>EJORDT</coden><abstract>► Under epistemic uncertainty a risk metric expected value differs from its nominal value. ► Separability and state-of-knowledge independence are necessary for coincidence. ► We extend Risk Achievement Worth to make it robust to epistemic uncertainty.
Risk achievement worth is one of the most widely utilized importance measures. RAW is defined as the ratio of the risk metric value attained when a component has failed over the base case value of the risk metric. Traditionally, both the numerator and denominator are point estimates. Relevant literature has shown that inclusion of epistemic uncertainty (i) induces notable variability in the point estimate ranking and (ii) causes the expected value of the risk metric to differ from its nominal value. We investigate the conditions under which the equality of the nominal and expected values of a reliability risk metric holds. We then study how the presence of epistemic uncertainty affects RAW and the associated ranking. We propose an extension of RAW (called ERAW) which allows one to obtain a ranking robust to epistemic uncertainty. We discuss the properties of ERAW and the conditions under which it coincides with RAW. We apply our findings to a probabilistic risk assessment model developed for the safety analysis of NASA lunar space missions.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.ejor.2012.05.008</doi><tpages>11</tpages></addata></record> |
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subjects | Applied sciences Decision analysis Decision theory. Utility theory epistemic Epistemology Estimates Exact sciences and technology Expected values importance Importance measures MATHEMATICS AND COMPUTING NASA Operational research Operational research and scientific management Operational research. Management science Probabilistic risk assessment Ranking RAW Reliability analysis Reliability theory. Replacement problems Risk Risk analysis Risk assessment Risk theory. Actuarial science Space exploration Studies Uncertainty Uncertainty analysis |
title | Composite multilinearity, epistemic uncertainty and risk achievement worth |
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