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 OJMSi  Vol.2 No.4 , October 2014
Partial Availability and RGBI Methods to Improve System Performance in Different Interval of Time: The Drill Facility System Case Study
Abstract: The main objective of this study is to propose a methodology to define the operational availability for a system in different interval of time based on Monte Carlo simulation. In addition, it is also an objective to identify critical equipment in such interval of time and define when carrying out inspections to detect and prevent failures. Nowadays, many software packages which apply Monte Carlo simulation based on reliability diagram block do not show the operational availability defined by interval of time. In most of cases, there’s no result that shows how system performs in specific interval of time. Depending on situation, it’s important to define the operational availability by different interval of time in order to follow up system performance along time. In order to solve such problem, it is proposed the “partial availability methodology” based on system age. Indeed, such method regards equipment age based in different period of time that will results in Partial Availability. That means, as instance, in case of two years of simulation there will be the cumulative operational availability and partial operational availability results for first and second years for example. Therefore, it is also important to define the inspection time in each interval of time (year) in order to detect possible equipment failure and define preventive maintenance to avoid such failures that will be performed by RGBI method. In order to show such methodologies, it will be carried out a drill facility case study which is required to define operational availability of the system on the first and second years as well as inspection time.
Cite this paper: Calixto, E. , Gilson, G. and Oliveira, A. (2014) Partial Availability and RGBI Methods to Improve System Performance in Different Interval of Time: The Drill Facility System Case Study. Open Journal of Modelling and Simulation, 2, 144-153. doi: 10.4236/ojmsi.2014.24016.
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