## 4 Discussion and Validation
### Human Factors in Notification Processes  
The data collection process of the empiric case study data became a lot more time-consuming than first anticipated. Its sole reason is traced back to human factors present in the notification processes that evidentially reduced the quality of the data significantly. This issue is clearly demonstrated by the simulated results. Use case Scenarios 1, 2, and 4 include the same failure rates extracted from the case study but with different MTTR values. In more detail, Scenario 1 includes MTTR values as presented in the notification process, Scenario 2 includes manipulated MTTR values considered as unreasonable extremes in the previous scenario, and Scenario 4 includes MTTR values extracted from the OREDA database [17]. Therefore, the volatile changes in operational behavior and significant differences in maintenance workload between these three scenarios are solely traced back to the MTTR values. Respectively, the maintenance workload (in hours) devoted  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Detection and** & **Corrective Events** & **Opportunistic Events** &
\begin{tabular}{c} **Corrective Maintenance** \\ **Reduction [\%]** \\ \end{tabular} \\ \hline
**50\%** & 3 & 8 & 72.727 \\ \hline
**60\%** & 3 & 8 & 72.727 \\ \hline
**70\%** & 6 & 5 & 45.454 \\ \hline
**80\%** & 7 & 4 & 36.363 \\ \hline
**90\%** & 8 & 3 & 27.272 \\ \hline
**100\%** & 11 & 0 & 0 \\ \hline \hline \end{tabular}
\end{table}
Table 12: The effect of proliferating detection and prediction levels.  
to corrective maintenance for Scenarios 1, 2, and 4 are 107,700, 44,055, and 3262 with associated operational availabilities of 37.756, 73.384, and 95.750%.  
From the authors' perspective, the main issue of incorporating human factors in the notification processes is traced back to the maintenance personnel's opportunity of developing a notification that is solely based on subjective perceptions, without any associated requirements concerning the level of details of the individual notifications. Following this, the simulated results also justify why the O&G companies keep using the OREDA database [17] and not their own empiric data in connection with analysis related to, e.g., technical integrity and risk. However, it is a paradox that case-specific data do not express the case of interest the best. Therefore, for the future, it shall be recommended that the notification processes avoid incorporating human factors, at least, reducing its impact by making the notification process (partial) automatic or based on a templated questionary with pre-defined alternatives the maintenance personnel is required to answer before the notification is considered as complete.  
At last, it is also important to emphasize that the failure data originating from the case study includes several components of one component, i.e., rotor, bearing, and seal. However, due to difficulties in differentiating between these specific components, the failure rates presented in this research do not take into consideration the number of each component. Illustratively, this means that this research estimates one failure rate composing all the failures associated with one type of component, without taking its population into consideration. Therefore, the failure rate assumes that failure of, for instance, one bearing, results in failure of all the bearings present in the case study at the same time.