Availability estimation of utility module in offshore plant depending on system configuration
- Authors
- Seo, Y.; Han, S.; Kang, K.; Noh, H.-J.; Park, S.; Jung, J.-Y.; Chang, D.
- Issue Date
- 2017
- Publisher
- CRC Press/Balkema
- Citation
- Safety and Reliability - Theory and Applications - Proceedings of the 27th European Safety and Reliability Conference, ESREL 2017, pp 2195 - 2202
- Pages
- 8
- Journal Title
- Safety and Reliability - Theory and Applications - Proceedings of the 27th European Safety and Reliability Conference, ESREL 2017
- Start Page
- 2195
- End Page
- 2202
- URI
- https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/8510
- DOI
- 10.1201/9781315210469-277
- ISSN
- 0000-0000
- Abstract
- This study estimated the availability of an air compressor & nitrogen generator system in a utility module to analyze the availability depending on its configuration. The utility module is one of essential modules in an offshore plant. It supplies water, air or some utilities to the offshore plant for safe and stable operation. This study only investigated the air compressor & nitrogen generator system in the utility module because it was one of important systems for safety. The air compressor increased the pressure of air up to 10 bar and the nitrogen generator separated nitrogen from the compressed air. This study employed three methods for the availability estimation: Reliability Block Diagram (RBD), Markov model, and Monte Carlo simulation. The former two belonged to an analytical approach and the later one was affiliated to a simulation approach. Three configurations were investigated depending on the structure of the major equipment (air compressor and nitrogen generator): 1 × 100%, 2 × 50%, and 2 × 100%. The results showed that the availabilities were almost same regardless the employed methods (RBD, Markov model, and Monte Carlo simulation) When the 2 × 100% configuration was employed, the availability was 1% higher than other configuration. This result meant that the redundancy increased the availability by 1% in the system. Although this study analyzed small part of the offshore plant, it was meaningful as the first step to estimate the availability of the offshore plant. ? 2017 Taylor & Francis Group, London.
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