## 2 Materials and Methods
### Pseudocode
Instead of relying on static time-based maintenance, the system integrates both fixed intervals and condition-based triggers. As soon as a machine reaches its predefined limit (e.g., 3000 operating hours for ball bearing replacement), the model automatically suggests the next available maintenance slot within the production schedule to minimise disruptions. Depending on the type of maintenance, different effects on machine condition can be observed. While reg \begin{table}
\begin{tabular}{c c c} \hline \hline
**Interval** & **Maintenance Measure** & \
\begin{tabular}{c} **Effect on Machine** \\ **Condition** \\ \end{tabular} \\ \hline Weekly &
\begin{tabular}{c} Lubrication of the drill \\ spindle \\ Inspection of the drill \\ spindle and screws \\ Replacement of ball \\ bearings (partial overhaul) \\ Replacement of spindle \\ components (partial overhaul) \\ After 10 years or 50,000 h \\ Full spindle overhaul \\ \end{tabular} & No change \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Maintenance measures and their effects on machine condition. Regular inspections maintain underline, while more extensive measures restore the wear reserve partially or completely. ular inspections and lubrication stabilise the machine condition, more extensive overhauls lead to a significant restoration of the wear reserve. The maintenance intervals shown in Table 2 serve as input parameters for the scheduling model. The system tracks machine hours, checks them against defined thresholds, and automatically integrates maintenance activities into the production plan when necessary. Figure 2 clearly shows that the drilling machine has almost reached its wear threshold, making scheduled maintenance necessary to prevent failure. The model not only recognises machines that have already reached the threshold value, but also reports at an early stage when a machine is approaching this value. This allows preventative measures to be taken before critical conditions occur. After planning, the model identifies machines with critical wear and tear and shows available time slots for maintenance. The planner chooses a suitable time slot and defines the type of maintenance and the expected reduction in the wear value. The maintenance is then integrated into the production plan, and the condition of the machine is updated. Figure 3 shows the complete reset of wear after maintenance on the drilling machine. The visualisation of the machine conditions is based on the current production orders in order to identify overloads at an early stage and counteract them in a focused manner [8]. This allows resources to be used efficiently, maintenance measures to be planned proactively and reactive measures to be minimised. At the same time, the analysis helps to ensure balanced machine utilisation and avoid long-term differences in wear between machines. ### Key Performance Indicators for Optimisation

The bar chart shown in Figure 4 presents the total machine load over the planning period. This total load is calculated as a combination of three factors:

* Operational Load--The amount of time a machine spends actively processing production orders. * Mechanical Stress--The workload intensity based on production parameters, such as cutting forces or thermal influences. * Additional Stress Factor--Production-specific influences, such as material properties or special manufacturing requirements. The selection of these three indicators is based on their practical relevance for maintenance planning. Together, they reflect both time utilisation and physical stress on the machines, providing a comprehensive picture of machine load. Combining them into a composite indicator supports intuitive visualisation and enables a direct comparison between machines. The number of indicators is deliberately limited to three to ensure clear interpretation without redundancy. The selected indicators are validated in collaboration with maintenance experts.