- Title
- Reliability analysis: assessment of hardware and human reliability
- Creator
- Mafu, Masakheke
- ThesisAdvisor
- Raubenheimer, L
- Subject
- Bayesian statistical decision theory
- Subject
- Reliability (Engineering)
- Subject
- Human machine systems
- Subject
- Probabilities
- Subject
- Markov processes
- Date
- 2017
- Type
- Thesis
- Type
- Masters
- Type
- MSc
- Identifier
- http://hdl.handle.net/10962/6280
- Identifier
- vital:21077
- Description
- Most reliability analyses involve the analysis of binary data. Practitioners in the field of reliability place great emphasis on analysing the time periods over which items or systems function (failure time analyses), which make use of different statistical models. This study intends to introduce, review and investigate four statistical models for modeling failure times of non-repairable items, and to utilise a Bayesian methodology to achieve this. The exponential, Rayleigh, gamma and Weibull distributions will be considered. The performance of the two non-informative priors will be investigated. An application of two failure time distributions will be carried out. To meet these objectives, the failure rate and the reliability functions of failure time distributions are calculated. Two non-informative priors, the Jeffreys prior and the general divergence prior, and the corresponding posteriors are derived for each distribution. Simulation studies for each distribution are carried out, where the coverage rates and credible intervals lengths are calculated and the results of these are discussed. The gamma distribution and the Weibull distribution are applied to failure time data.The Jeffreys prior is found to have better coverage rate than the general divergence prior. The general divergence shows undercoverage when used with the Rayleigh distribution. The Jeffreys prior produces coverage rates that are conservative when used with the exponential distribution. These priors give, on average, the same average interval lengths and increase as the value of the parameter increases. Both priors perform similar when used with the gamma distribution and the Weibull distribution. A thorough discussion and review of human reliability analysis (HRA) techniques will be considered. Twenty human reliability analysis (HRA) techniques are discussed; providing a background, description and advantages and disadvantages for each. Case studies in the nuclear industry, railway industry, and aviation industry are presented to show the importance and applications of HRA. Human error has been shown to be the major contributor to system failure.
- Format
- 155 pages, pdf
- Publisher
- Rhodes University, Faculty of Science, Statistics
- Language
- English
- Rights
- Mafu, Masakheke
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| Thumbnail | File | Description | Size | Format | |||
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