# Real-Time Maintenance Optimization with Industrial Internet of Things
## 4 Results
### IIoT Technologies-Supported Real-Time Optimization of Maintenance Operations  
The conventional maintenance optimization solution outlined in Section 4.1 has the disadvantage that maintenance tasks for different system components (entities) are carried out based on a predefined or optimized maintenance period (cycle time). The advantage of this approach is its simplicity and predictability, as maintenance operations occur at regular intervals. However, if real-time data from the system's structural resources (production and logistics resources) are available, maintenance activities can be optimized by eliminating unnecessary maintenance operations, ensuring that only necessary maintenance is performed. At the same time, this approach ensures that the system's reliability remains at a level that guarantees required productivity. Real-time optimization based on these data forms the foundation of the IIoT-based solution presented in the previous chapter. In this IIoT-based real-time optimization model, the input data are the same as the input data used in the case study demonstrating the conventional optimization task (see Figure 2 and Table 3). If real-time state information of the manufacturing system's resources is available, it is possible to determine the optimal maintenance period in real-time, taking this information into account. The maintenance period is dynamically changing within the time window of the analysis. Using the mathematical model presented in Section 3.1, real-time optimization simulation can be performed in the production system defined by Figure 2 and Table 3. The results of this simulation are illustrated in Figures 9-11. Figure 9 illustrates the case where the length of each maintenance period must be optimized in real-time in such a way that the reliability of the manufacturing system does not fall below 60%. In this case, the minimum length of the optimized maintenance periods is 3.175 h, the average length is 3.712 h, the maximum length is 6.725 h, while the standard deviation is 0.752 h. In this case, the analyzed 20 maintenance periods covered 74.25 h of production time. Figure 8: The relationship between the maintenance periods and the specific profit depending on the maintenance cost and the income based on productivity. Figure 10 illustrates the case where the length of each maintenance period must be optimized in real-time in such a way that the reliability of the manufacturing system does  
Figure 11: The system reliability function over 20 maintenance periods, given a predefined minimum system reliability of 95%, and real-time optimization based on real-time state information enabled by IIoT technologies. Figure 9: The system reliability function over 20 maintenance periods, given a predefined minimum system reliability of 60%, and real-time optimization based on real-time state information enabled by IIoT technologies. not fall below 75%. In this case, the minimum length of the optimized maintenance periods is 2.925 h, the average length is 3.452 h, the maximum length is 5.05 h, while the standard deviation is 0.462 h. In this case, the analyzed 20 maintenance periods covered 69.05 h of production time. Figure 11 illustrates the case where the length of each maintenance period must be optimized in real-time in such a way that the reliability of the manufacturing system does not fall below 95%. In this case, the minimum length of the optimized maintenance periods is 2.6 h, the average length is 3.099 h, the maximum length is 3.725 h, while the standard deviation is 0.314 h. In this case, the analyzed 20 maintenance periods covered 61.97 h of production time. By analyzing the characteristics of the maintenance periods in detail (see Figure 12), it can be clearly observed that an increase in the predefined minimum system reliability results in a notable reduction in the statistical parameters of the maintenance periods, including their minimum, maximum, average, and standard deviation values.