Determination Method Based on Bayesian Theory for Equipment Field Failure Rate
| Autor: | Miao Guo, Xinlei Li, Jianghong Jin, Wenze Xiong |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
020901 industrial engineering & automation Computer science Bayesian probability 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Failure rate 02 engineering and technology Data mining computer.software_genre computer |
| Zdroj: | 2019 Chinese Control Conference (CCC). |
| DOI: | 10.23919/chicc.2019.8866651 |
| Popis: | Aiming to the problems of domestic database missing, strong universality with insufficient specificity in the abroad database and the utilization of sample information collected by enterprises, the thesis studies how to obtain accurate field failure rate of equipment. Bayesian method is selected by analyzing and comparing various reliability data processing methods. Bayesian method is applied to modify the database failure data to obtain a more practical equipment failure rate by taking the equipment failure rate provided by foreign database as a priori data, and collecting the related equipment failure rate of enterprises as sample data. In this thesis, it is proved that the failure rate estimation based on the Bayesian Method is more accurate and reasonable by comparing with the failure rate values estimated by classical points estimate method and the failure rate values inquired from the abroad database. |
| Databáze: | OpenAIRE |
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