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 |
File
Original bundle
1 - 1 of 1
No Thumbnail Available
- Name:
- Lei_iastate_0097M_16392.pdf
- Size:
- 1.19 MB
- Format:
- Adobe Portable Document Format
- Description: