RELIABILITY ANALYSIS OF PRIMARY AND PURIFICATION PUMPS IN RSG-GAS USING MONTE CARLO SIMULATION APPROACH
Entin Hartini, Hery Adrial, Santosa Pujiarta
Abstract
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Entin Hartini, Hery Adrial, Santosa Pujiarta
Abstract
Open-access reader
Reliability and maintenance play an important role in ensuring successful operation of a system. Reliability analysis is often used to determine the probability whether or not a system is functioning. However, limited available data and information are causing uncertainties and inaccuracies on component parameters. The purpose of this study is to conduct component/system reliability analysis using Monte Carlo simulation-based method. This method enables us to estimate the reliability of components/systems including parameter uncertainty and imprecision. It is also useful to predict and evaluate maintenance decisions related to reliability. Monte Carlo method employs random number generation based on the probability of the distribution of processed data, of which then validated with real available data to ensure the simulation condition is relatively similar to real-life condition. The data used in this research is failure data on RSG-GAS components/systems for core configuration number of 81 to 95, accumulated from year 2013 to 2018. The results show that reliability values of components JE01/AP01-02 on TTF 233.619 is 0.579 while for components KBE01/AP-01-02 in TTF 185.38 is 0.368.The component reliability value is 60%, which implies that maintenance may be performed after 225 days and 100 days for componentsJE01/AP01-02 and KBE01/AP01-02, respectively.Keywords: Reliability, Monte Carlo, Component damage, RSG-GAS
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Reliability and maintenance play an important role in ensuring successful operation of a system. Reliability analysis is often used to determine the probability whether or not a system is functioning. However, limited available data and information are causing uncertainties and inaccuracies on component parameters. The purpose of this study is to conduct component/system reliability analysis using Monte Carlo simulation-based method. This method enables us to estimate the reliability of components/systems including parameter uncertainty and imprecision. It is also useful to predict and evaluate maintenance decisions related to reliability. Monte Carlo method employs random number generation based on the probability of the distribution of processed data, of which then validated with real available data to ensure the simulation condition is relatively similar to real-life condition. The data used in this research is failure data on RSG-GAS components/systems for core configuration number of 81 to 95, accumulated from year 2013 to 2018. The results show that reliability values of components JE01/AP01-02 on TTF 233.619 is 0.579 while for components KBE01/AP-01-02 in TTF 185.38 is 0.368.The component reliability value is 60%, which implies that maintenance may be performed after 225 days and 100 days for componentsJE01/AP01-02 and KBE01/AP01-02, respectively.Keywords: Reliability, Monte Carlo, Component damage, RSG-GAS
Key concepts: Monte Carlo method, Reliability (semiconductor), Reliability engineering, Component (thermodynamics), Computer science, Statistics, Engineering, Mathematics