Reliability Analysis in Ship’s Critical Machinery
Reliability analysis in ship’s critical machinery
Objectives 1. Implement Markov process to identify availability of the engines of a vessel. 2. Using Monte Carlo simulation technique to model the Markov process using non-continuous transition rates. 3. Using the simulation model, calculate different reliability cost and worth, using numerous what-if scenarios.
Objectives #1: Implement Markov process to identify availability of the engines of a vessel.
Markov Process
A Markov model of a system operation process is proposed and its selected parameters are determined. A series-parallel multi-state system is considered and its reliability and availability are found. Lastly, the asymptotic approach to reliability and availability of the multi-state series-parallel system in its operation process is applied.
Most maritime systems are very complex and it is difficult to analyze their reliability and availability in their time-varying operation processes. The huge number of components and their operating complexity created difficulty in the evaluation of the reliability and availability of these systems. A very important technique proposed to simplify the reliability and availability evaluation of large systems is the asymptotic approach.
Accordingly, reliability analysis and evaluation is applied to the Markov model of these changing systems operation states. In this model, the variability of system components reliability characteristics is pointed by introducing the components’ conditional reliability functions determined by the system operation states.
The engine system of the vessel is simplified as shown in Figure 1 to illustrate the application.
ME
A/E S
A/E P
Figure 1. Simplified system reliability block diagram
System | State | Engine | | | ME | A/E P | A/E S | Available | 1 | 1 | 1 | 1 | | 2 | 1 | 0 | 1 | | 3 | 1 | 1 | 0 | Unavailable | 4 | 0 | 1 | 1 | | 5 | 1 | 0 | 0 | | 6 | 0 | 1 | 0 | | 7 | 0 | 0 | 1
Objectives 1. Implement Markov process to identify availability of the engines of a vessel. 2. Using Monte Carlo simulation technique to model the Markov process using non-continuous transition rates. 3. Using the simulation model, calculate different reliability cost and worth, using numerous what-if scenarios.
Objectives #1: Implement Markov process to identify availability of the engines of a vessel.
Markov Process
A Markov model of a system operation process is proposed and its selected parameters are determined. A series-parallel multi-state system is considered and its reliability and availability are found. Lastly, the asymptotic approach to reliability and availability of the multi-state series-parallel system in its operation process is applied.
Most maritime systems are very complex and it is difficult to analyze their reliability and availability in their time-varying operation processes. The huge number of components and their operating complexity created difficulty in the evaluation of the reliability and availability of these systems. A very important technique proposed to simplify the reliability and availability evaluation of large systems is the asymptotic approach.
Accordingly, reliability analysis and evaluation is applied to the Markov model of these changing systems operation states. In this model, the variability of system components reliability characteristics is pointed by introducing the components’ conditional reliability functions determined by the system operation states.
The engine system of the vessel is simplified as shown in Figure 1 to illustrate the application.
ME
A/E S
A/E P
Figure 1. Simplified system reliability block diagram
System | State | Engine | | | ME | A/E P | A/E S | Available | 1 | 1 | 1 | 1 | | 2 | 1 | 0 | 1 | | 3 | 1 | 1 | 0 | Unavailable | 4 | 0 | 1 | 1 | | 5 | 1 | 0 | 0 | | 6 | 0 | 1 | 0 | | 7 | 0 | 0 | 1