Simulation of key performance characteristics under uncertainty
Abstract The engineering designer frequently has to deal with multiple uncertainties, especially at the early design stages or when working on products for which the body of knowledge is incomplete. Wash performance of dishwashers is one such case. This paper demonstrates the application of the desi...
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Veröffentlicht in: | Proceedings of the Institution of Mechanical Engineers. Part B, Journal of engineering manufacture Journal of engineering manufacture, 2005-01, Vol.219 (1), p.151-162 |
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creator | Pons, D J Raine, J K |
description | Abstract
The engineering designer frequently has to deal with multiple uncertainties, especially at the early design stages or when working on products for which the body of knowledge is incomplete. Wash performance of dishwashers is one such case. This paper demonstrates the application of the design for system integrity (DSI) methodology to create a model to help to predict wash performance. This is a complex problem because of the diverse uncertainties: stochastic, epistemic, and abstraction. The DSI model embodied the belief that two principal mechanisms contribute to wash performance: the effectiveness of soil removal, and the effectiveness of the rinse process (i.e. lack of re-deposition of soil). The model was calibrated against wash data from a known machine and then predicted the wash performance of a different brand of machine with qualitative differences in geometry. The results show that it is possible to develop models for highly uncertain systems, and this has important implications for early engineering design among other domains. Being able to simulate performance under considerable uncertainty, even if imperfectly, is potentially an important tool for the early design stages as it could indicate, firstly, promising design avenues and, secondly, the risk in the design and the degree to which design issues have been resolved. |
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The engineering designer frequently has to deal with multiple uncertainties, especially at the early design stages or when working on products for which the body of knowledge is incomplete. Wash performance of dishwashers is one such case. This paper demonstrates the application of the design for system integrity (DSI) methodology to create a model to help to predict wash performance. This is a complex problem because of the diverse uncertainties: stochastic, epistemic, and abstraction. The DSI model embodied the belief that two principal mechanisms contribute to wash performance: the effectiveness of soil removal, and the effectiveness of the rinse process (i.e. lack of re-deposition of soil). The model was calibrated against wash data from a known machine and then predicted the wash performance of a different brand of machine with qualitative differences in geometry. The results show that it is possible to develop models for highly uncertain systems, and this has important implications for early engineering design among other domains. Being able to simulate performance under considerable uncertainty, even if imperfectly, is potentially an important tool for the early design stages as it could indicate, firstly, promising design avenues and, secondly, the risk in the design and the degree to which design issues have been resolved.</description><identifier>ISSN: 0954-4054</identifier><identifier>EISSN: 2041-2975</identifier><identifier>DOI: 10.1243/095440505X7993</identifier><language>eng</language><publisher>London, England: SAGE Publications</publisher><subject>Applied sciences ; Design engineering ; Dishwashing machines ; Epistemology ; Exact sciences and technology ; Mechanical engineering. Machine design ; Stochastic models ; Systems design</subject><ispartof>Proceedings of the Institution of Mechanical Engineers. Part B, Journal of engineering manufacture, 2005-01, Vol.219 (1), p.151-162</ispartof><rights>2005 Institution of Mechanical Engineers</rights><rights>2005 INIST-CNRS</rights><rights>Copyright Mechanical Engineering Publications, Ltd. Jan 2005</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c497t-1604237395b06ea937567ba90fc3b40f22bb6c07f73e994cc138a60ae94497a83</citedby><cites>FETCH-LOGICAL-c497t-1604237395b06ea937567ba90fc3b40f22bb6c07f73e994cc138a60ae94497a83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1243/095440505X7993$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1243/095440505X7993$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>314,780,784,4023,21818,27922,27923,27924,43620,43621</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=16447210$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Pons, D J</creatorcontrib><creatorcontrib>Raine, J K</creatorcontrib><title>Simulation of key performance characteristics under uncertainty</title><title>Proceedings of the Institution of Mechanical Engineers. Part B, Journal of engineering manufacture</title><description>Abstract
The engineering designer frequently has to deal with multiple uncertainties, especially at the early design stages or when working on products for which the body of knowledge is incomplete. Wash performance of dishwashers is one such case. This paper demonstrates the application of the design for system integrity (DSI) methodology to create a model to help to predict wash performance. This is a complex problem because of the diverse uncertainties: stochastic, epistemic, and abstraction. The DSI model embodied the belief that two principal mechanisms contribute to wash performance: the effectiveness of soil removal, and the effectiveness of the rinse process (i.e. lack of re-deposition of soil). The model was calibrated against wash data from a known machine and then predicted the wash performance of a different brand of machine with qualitative differences in geometry. The results show that it is possible to develop models for highly uncertain systems, and this has important implications for early engineering design among other domains. Being able to simulate performance under considerable uncertainty, even if imperfectly, is potentially an important tool for the early design stages as it could indicate, firstly, promising design avenues and, secondly, the risk in the design and the degree to which design issues have been resolved.</description><subject>Applied sciences</subject><subject>Design engineering</subject><subject>Dishwashing machines</subject><subject>Epistemology</subject><subject>Exact sciences and technology</subject><subject>Mechanical engineering. Machine design</subject><subject>Stochastic models</subject><subject>Systems design</subject><issn>0954-4054</issn><issn>2041-2975</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqNkctLw0AQxhdRsFavnoOgHiR134-TSPEFBQ8qeAuTdVdT06TuJof-925pwQcincPMYX7fNzAfQocEjwjl7BwbwTkWWDwrY9gWGlDMSU6NEttosFzmact30V6MU5xKMTZAFw_VrK-hq9oma3327hbZ3AXfhhk01mX2DQLYzoUqdpWNWd-8uJC6daGDqukW-2jHQx3dwXoO0dP11eP4Np_c39yNLye55UZ1OZGYU6aYESWWDgxTQqoSDPaWlRx7SstSWqy8Ys4Ybi1hGiQGZ3jSg2ZDdLrynYf2o3exK2ZVtK6uoXFtHwvFGRdSapnIk39JqpUmgugNQCkYT2_aAGSYKZzAo1_gtO1Dk_5SECMIN1rTBI1WkA1tjMH5Yh6qGYRFQXCxDLL4GWQSHK9dIVqofUjJVPFLJTlXlCyvn624CK_u2-W_XT8BMF6njA</recordid><startdate>20050101</startdate><enddate>20050101</enddate><creator>Pons, D J</creator><creator>Raine, J K</creator><general>SAGE Publications</general><general>Mechanical Engineering Publications</general><general>SAGE PUBLICATIONS, INC</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TB</scope><scope>7XB</scope><scope>88I</scope><scope>8AF</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F28</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M2P</scope><scope>M7S</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>7SC</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20050101</creationdate><title>Simulation of key performance characteristics under uncertainty</title><author>Pons, D J ; Raine, J K</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c497t-1604237395b06ea937567ba90fc3b40f22bb6c07f73e994cc138a60ae94497a83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Applied sciences</topic><topic>Design engineering</topic><topic>Dishwashing machines</topic><topic>Epistemology</topic><topic>Exact sciences and technology</topic><topic>Mechanical engineering. Machine design</topic><topic>Stochastic models</topic><topic>Systems design</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pons, D J</creatorcontrib><creatorcontrib>Raine, J K</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>STEM Database</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Science Database (ProQuest)</collection><collection>Engineering Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><collection>Computer and Information Systems Abstracts</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><jtitle>Proceedings of the Institution of Mechanical Engineers. Part B, Journal of engineering manufacture</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pons, D J</au><au>Raine, J K</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Simulation of key performance characteristics under uncertainty</atitle><jtitle>Proceedings of the Institution of Mechanical Engineers. Part B, Journal of engineering manufacture</jtitle><date>2005-01-01</date><risdate>2005</risdate><volume>219</volume><issue>1</issue><spage>151</spage><epage>162</epage><pages>151-162</pages><issn>0954-4054</issn><eissn>2041-2975</eissn><abstract>Abstract
The engineering designer frequently has to deal with multiple uncertainties, especially at the early design stages or when working on products for which the body of knowledge is incomplete. Wash performance of dishwashers is one such case. This paper demonstrates the application of the design for system integrity (DSI) methodology to create a model to help to predict wash performance. This is a complex problem because of the diverse uncertainties: stochastic, epistemic, and abstraction. The DSI model embodied the belief that two principal mechanisms contribute to wash performance: the effectiveness of soil removal, and the effectiveness of the rinse process (i.e. lack of re-deposition of soil). The model was calibrated against wash data from a known machine and then predicted the wash performance of a different brand of machine with qualitative differences in geometry. The results show that it is possible to develop models for highly uncertain systems, and this has important implications for early engineering design among other domains. Being able to simulate performance under considerable uncertainty, even if imperfectly, is potentially an important tool for the early design stages as it could indicate, firstly, promising design avenues and, secondly, the risk in the design and the degree to which design issues have been resolved.</abstract><cop>London, England</cop><pub>SAGE Publications</pub><doi>10.1243/095440505X7993</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Applied sciences Design engineering Dishwashing machines Epistemology Exact sciences and technology Mechanical engineering. Machine design Stochastic models Systems design |
title | Simulation of key performance characteristics under uncertainty |
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