Static and dynamic fault tree analysis with application to hybrid vehicle systems and supply chains

dc.contributor.advisor Cameron MacKenzie
dc.contributor.author Lei, Xue
dc.contributor.department Industrial and Manufacturing Systems Engineering
dc.date 2018-08-11T17:36:12.000
dc.date.accessioned 2020-06-30T03:03:13Z
dc.date.available 2020-06-30T03:03:13Z
dc.date.copyright Sun Jan 01 00:00:00 UTC 2017
dc.date.embargo 2001-01-01
dc.date.issued 2017-01-01
dc.description.abstract <p>One of the most challenging parts of reliability analysis is building a reliability model of the system. Reliability block diagram, Markov models, and fault tree analysis are some of the most common techniques for constructing a reliability model. Fault tree analysis provides a way to combine components, which together can cause system failure. This research uses both static and dynamic fault trees to quantify the reliability of a hybrid vehicle system and to analyze supply chain risk. The hybrid vehicle combines a mechanical power source, such as the internal combustion engine (gasoline engine or diesel engine), and an electric power source (electric motor) to take advantage of two power sources and compensate from each source. The hybrid system’s complexity and non-mature technology carry potential risks for the vehicle. This research uses a static fault tree to analyze the reliability of the 2004 Toyota Prius under different operational modes. We apply Bayesian analysis that combines survey data to estimate the reliability of the hybrid vehicle’s battery. Supply chain risk analysis is increasingly becoming an important field and supply chain risk models help identify significant risks that can occur and the consequences if those risks occur. We use dynamic fault trees, which are relatively new in reliability analysis, to understand the timing of potential failures in different types of supply chains. We estimate failure rates for each supply chain under different production scenarios and simulate delivery time for the supply chain.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/etd/15345/
dc.identifier.articleid 6352
dc.identifier.contextkey 11051277
dc.identifier.doi https://doi.org/10.31274/etd-180810-4973
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath etd/15345
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/29528
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/etd/15345/Lei_iastate_0097M_16392.pdf|||Fri Jan 14 20:39:36 UTC 2022
dc.subject.disciplines Industrial Engineering
dc.subject.keywords Bayesian analysis
dc.subject.keywords dynamic fault tree
dc.subject.keywords hybrid vehicle system
dc.subject.keywords reliability analysis
dc.subject.keywords static fault tree
dc.subject.keywords supply chain risk
dc.title Static and dynamic fault tree analysis with application to hybrid vehicle systems and supply chains
dc.type thesis en_US
dc.type.genre thesis en_US
dspace.entity.type Publication
relation.isOrgUnitOfPublication 51d8b1a0-5b93-4ee8-990a-a0e04d3501b1
thesis.degree.discipline Industrial and Manufacturing Systems Engineering
thesis.degree.level thesis
thesis.degree.name Master of Science
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