## 4 Results and Discussion
### Impact on Maintenance Task Prioritization, Planning, and Scheduling  
Determining the maintenance intervals in a risk-based maintenance program is based on the mean time between failures and consequences. Although the theory highlights that determining maintenance intervals in RBM is not a one-time task and requires regular review and reassessment to adapt to changing equipment conditions, the practices are more static and a one-time task. Some practices take the time between the last two failure events and consider it a maintenance interval. Some define the maintenance interval based on the consequences to avoid black-swan events. Some take the mean time between failure (MTBF) or use Weibull analysis to find the time between the failure events. MTBF is calculated as the total operating time divided by the number of failures, while Weibull's TBF is estimated by fitting the failure data to the Weibull distribution. Some use Weibull analysis as reliability-centered maintenance and adjust the time interval based on its consequence class, whereas the high consequence class requires a shorter maintenance interval. The maintenance engineer or planner must perform three functions: (1) prioritize maintenance work order, (2) schedule preventive maintenance work order, and (3) estimate maintenance intervals (especially in the project phase). \begin{table}
\begin{tabular}{l l l l} \hline \hline
**Aspect** & \begin{tabular}{l} **Safety and Production** \\ **Consequence** \\ \end{tabular} & \
\begin{tabular}{l} **OPEX and Maintenance** \\ **Related Consequence** \\ \end{tabular} &
\begin{tabular}{l} **CAPEX** \\ **CAPEX** \\ \end{tabular} \\ \hline System with no advanced maintenance concepts & High Consequence & High & Low \\ Instrumented system with predictive maintenance & Medium Consequence & Medium & Medium \\ System with redundancy and heavy instrumentation & Low Consequence & Medium-High & High \\ \hline \hline \end{tabular}
\end{table} 
Table 13: System design and related consequences. Maintenance planners usually prioritize corrective maintenance work orders after a functional failure is recorded, based on consequences to minimize downtime and ensure efficient resource allocation. The use of condition monitoring and predictive maintenance shifted the focus to potential failures rather than functional failures. In other words, it turned the focus from only depending on consequences to depending on the risk matrix, where both consequence and failure likelihood are important. Therefore, prioritization of maintenance tasks requires two more criteria besides the failure consequence, as illustrated in Figure 8: (1) condition criticality where condition class is determined and (2) the deterioration or propagation class, which describes the speed or future propagation rate. The maintenance schedule for preventive maintenance tasks is usually created for tasks that should be performed and can be performed. The \"remaining time to failure\" and failure consequences determine what task should be performed first. The predefined maintenance events or opportunistic maintenance events and resource availability (spare parts, manning, tools) determine what can be achieved and when. The use of Industry 4.0 technology and emerging practices have impacted all these scheduling factors. However, the most affected scheduling factor is the \"remaining time to failure\" as condition-based maintenance and predictive maintenance provide different numbers compared to reliability and risk-based numbers, as illustrated in Figure 9. The reliability-based estimate of the remaining time to failure depends on historical data; however, the condition-based estimate of the remaining time depends on the extrapolations of the current condition data (including near-past) and the functional failure threshold. In addition, the predictive estimate of the remaining time to failure depends on historical data, condition data, and future loading and operating data.