Selection of optimal target reliability in RBDO through reliability-based design for market systems (RBDMS) and application to electric vehicle design
DC Field | Value | Language |
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dc.contributor.author | Lee, Ungki | - |
dc.contributor.author | Kang, Namwoo | - |
dc.contributor.author | Lee, Ikjin | - |
dc.date.available | 2021-02-22T05:45:47Z | - |
dc.date.issued | 2019-09 | - |
dc.identifier.issn | 1615-147X | - |
dc.identifier.issn | 1615-1488 | - |
dc.identifier.uri | https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/2842 | - |
dc.description.abstract | Reliability-based design optimization (RBDO) allows decision-makers to achieve target reliability in product performance under engineering uncertainties. However, existing RBDO studies assume the target reliability as a given parameter and do not explain how to determine the optimal target reliability. From the perspective of the market, designing a product with high target reliability can satisfy many customers and increase market demand, but it can generate a large cost leading to profit reduction of the company. Therefore, the target reliability should be a decision variable which needs to be found to maximize the company profit. This paper proposes a reliability-based design for market systems (RBDMS) framework by integrating RBDO and design for market system (DMS) approaches to find the optimal target reliability. The proposed RBDMS framework is applied to electric vehicle (EV) design problems to validate effect of the target reliability on company profit-or market share-and engineering performances of EV. Several observations about the optimal target reliability are presented from the case study with various scenarios. From the EV design case study, it is verified that the proposed RBDMS framework is an effective way of finding the optimal target reliability that maximizes the company profit, and the optimal target reliability varies depending on the situation of market and competitors. | - |
dc.format.extent | 15 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | SPRINGER | - |
dc.title | Selection of optimal target reliability in RBDO through reliability-based design for market systems (RBDMS) and application to electric vehicle design | - |
dc.type | Article | - |
dc.publisher.location | 미국 | - |
dc.identifier.doi | 10.1007/s00158-019-02245-3 | - |
dc.identifier.scopusid | 2-s2.0-85064158000 | - |
dc.identifier.wosid | 000480601400006 | - |
dc.identifier.bibliographicCitation | STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, v.60, no.3, pp 949 - 963 | - |
dc.citation.title | STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION | - |
dc.citation.volume | 60 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 949 | - |
dc.citation.endPage | 963 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Mechanics | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Engineering, Multidisciplinary | - |
dc.relation.journalWebOfScienceCategory | Mechanics | - |
dc.subject.keywordPlus | LITHIUM-ION | - |
dc.subject.keywordPlus | UNCERTAINTY QUANTIFICATION | - |
dc.subject.keywordPlus | CAPACITY FADE | - |
dc.subject.keywordPlus | OPTIMIZATION | - |
dc.subject.keywordPlus | BATTERIES | - |
dc.subject.keywordPlus | MODEL | - |
dc.subject.keywordPlus | AEROELASTICITY | - |
dc.subject.keywordPlus | PROBABILITY | - |
dc.subject.keywordPlus | EFFICIENCY | - |
dc.subject.keywordPlus | REDUCTION | - |
dc.subject.keywordAuthor | Reliability-based design optimization (RBDO) | - |
dc.subject.keywordAuthor | Design for market systems (DMS) | - |
dc.subject.keywordAuthor | Electric vehicles | - |
dc.subject.keywordAuthor | Target reliability | - |
dc.subject.keywordAuthor | Uncertainty | - |
dc.identifier.url | https://link.springer.com/article/10.1007%2Fs00158-019-02245-3 | - |
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