The rapidly increasing loss of industrial accidents has become a big barrier to the development of modern industry. Therefore, safety and reliability in the industry should be treated seriously. Although there are many achievements in safety and reliability research, still many challenges are waiting for people to address. Human reliability is one of the most representative challenges. The source idea and methodology of human reliability are very different with facility reliability analysis, so in most system reliability analysis, facility reliability and human reliability are isolated with each other, and sometimes, human reliability is even neglected, which decrease the quality of system reliability analysis. However, according to many safety reports, human factors are always playing the root reason or one of the root reasons to activate the accidents. Regarding that, the integrated model, which involves human reliability and facility reliability, should be constructed. Therefore, in this Ph.D. research, a Markov chain based mathematical model, which contains human reliability and facility reliability, is established. Besides, only a simple model is not enough in solving the integrated reliability analysis problem, so the mathematical will be taken in optimization to find the best solutions for system reliability with the consideration on reliability requirements and budget requirements. Afterwards, based on the optimized result on human reliability, a Cognitive Reliability and Error Analysis Method (CREAM) based method is adopted to predict the real human reliability data, and if the real data fails to meet the optimized human reliability data, the CREAM will be used as a method to reasonably and logically provide a variety of human reliability promotion plans for people use. Finally, facing those plans, a decision supporting model should be built to help people choose the most reasonable plan for current use and future updating. Overall, an integrated model for both human and facility factors is constructed for industry use. This new proposed model has been tested on Beihai LNG Terminal in Guangxi China.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:752653 |
| Date | January 2018 |
| Creators | Zhang, Renyou |
| Publisher | University of Aberdeen |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=237093 |
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