# Fleet Resilience: Evaluating Maintenance Strategies in Critical Equipment
## 4 Case Study
### Simulation and Sensitivity Studies  
In the second stage, the sensitivity analysis one, various scenarios were proposed in order to study the behavior of the resilience index in relation to changes in the maintenance strategy. These scenarios can be divided into three groups: (i) the establishment of a simultaneous preventive maintenance plan for the nine items of critical equipment. These preventive interventions have a duration of 6 h and are applied with three different frequencies (3, 6 and 9 months); (ii) preventive interventions in each of the items of critical equipment separately, with three different durations (6, 9 and 12 h) and the same frequencies mentioned above; (iii) increase in redundancy in the critical fleet, incorporating, separately, one piece of equipment to each of the sub-fleets of drills to measure the behavior of the resilience index in the sub-fleet, fleet and in the extraction system as a whole. These scenarios totalize nine settings for the Class I experiments and 81 experiments for the Class II experiments. For type (iii) there are three experiments. Each Monte Carlo experiment was run with 1000 iterations for each scenario and the R-MES suite was used for this purpose. Figure 10 shows the behavior of the resilience index at the system level with the experiments of category (i). Figure 9: Actual availability of the extraction fleet. Figure 11 shows the behavior of the resilience indexes, for each sub-fleet, considering the preventive maintenance according to frequencies indicated for critical equipment. In the second set of experiments, simulations were carried out considering each of the nine critical equipment separately, preventive interventions with three different durations (6, 12 and 18 h), and with three frequencies of application between them (3, 9 and 12 months). Tables 3-5 show the results of these experiments. Figure 11: Resilience indexes of each sub-fleet with preventive maintenance in critical equipment. Figure 10: System resilience index with preventive maintenance on critical equipment. Firstly, it is noted that in general, significant increases in resilience are achieved by applying preventive maintenance. In general, the resilience values obtained from such \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **3 Months** & **6 Months** & **9 Months** & **Average** \\ \hline D07 & 72\% & 73\% & 74\% & 73\% \\ \hline D05 & 73\% & 74\% & 74\% & 74\% \\ \hline D08 & **75\%** & **75\%** & 73\% & 74\% \\ \hline H25 & **75\%** & 74\% & 73\% & 74\% \\ \hline S02 & 73\% & 74\% & **75\%** & 74\% \\ \hline H34 & 73\% & 74\% & 74\% & 74\% \\ \hline H34 & 74\% & 73\% & **75\%** & 74\% \\ \hline H31 & **75\%** & 73\% & 72\% & 73\% \\ \hline H04 & 73\% & 72\% & 72\% & 72\% \\ \hline Ave. & 74\% & 74\% & 74\% & 74\% \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Simulation experiment result: planned maintenance to each equipment (duration: 12 h). \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **3 Months** & **6 Months** & **9 Months** & **Average** \\ \hline D07 & 73\% & 72\% & 76\% & 74\% \\ \hline D05 & 75\% & 73\% & **76\%** & 74\% \\ \hline D08 & 74\% & 75\% & 75\% & 75\% \\ \hline H25 & **77\%** & 73\% & 75\% & 75\% \\ \hline S02 & 73\% & 75\% & **76\%** & 75\% \\ \hline H34 & 75\% & **76\%** & 75\% & 75\% \\ \hline H43 & 73\% & 72\% & **76\%** & 74\% \\ \hline H31 & 70\% & 72\% & 70\% & 71\% \\ \hline H04 & 75\% & 72\% & 70\% & 72\% \\ \hline Ave. & 74\% & 73\% & 74\% & 74\% \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Simulation experiment result: planned maintenance to each equipment (duration: 6 h).